Steig’s Trick

Please note: The author of this post is Ryan O . . . not Steve. As people have lately displayed a tendency to attribute what I write to Steve, I figured the disclaimer was appropriate.

Steve: Feb 9, 2011 – some of Ryan’s language, including the original title, breached blog policies and has been edited accordingly.
***

Some of you may have noticed that Eric Steig has a new post on our paper at RealClimate. In the past when I have wished to challenge Eric on something, I generally have responded at RealClimate. In this case, a more detailed response is required, and a simple post at RC would be insufficient. Based on the content, it would not have made it past moderation anyway.

Lest the following be entirely one-sided, I should note that most of my experiences with Eric in the past have been positive. He was professional and helpful when I was asking questions about how exactly his reconstruction was performed and how his verification statistics were obtained. My communication with him following acceptance of our paper was likewise friendly. While some of the public comments he has made about our paper have fallen far short of being glowing recommendations, Eric has every right to argue his point of view and I do not begrudge his doing so. I should also note that over the past week I was contacted by an editor from National Geographic, who mentioned in passing that he was referred to me by Eric. This was quite gracious of Eric, and I honestly appreciated the gesture.

However, once Eric puts on his RealClimate hat, his demeanor is something else entirely. Again, he has every right to blog about why he feels our paper is something other than how we have characterized it (just as we have every right to disagree). However, what he does not have the right to do is to defend his point of view by [snip] misrepresenting facts.

In other words, in his latest post, Eric crossed the line.

Let us examine how (with the best, of course, saved for last).

***

The first salient point is that Eric still doesn’t get it. The whole purpose of our paper was to demonstrate that if you properly use the data that S09 used, then the answer changes in a significant fashion. This is different than claiming that this particular method (whereby satellite data and ground station data are used together in RegEM) provides a more accurate representation of the [unknown] truth than other methods. We have not (and will not) make such a claim. The only claim we make is – given the data and regression method used by S09 – that the answer is different when the method by which the data are combined is properly employed. Period.

The question about whether the proper use of the AVHRR and station data sets yield an accurate representation of the temperature history of Antarctica is an entirely separate topic. To be sure, it is an important one, and it is a legitimate course of scientific inquiry for Eric to argue that our West Antarctic results are incorrect based on independent analyses. What is entirely, wholly, and completely not legitimate is to use those same arguments to defend the method of his paper, as the former makes no statement on the latter.

Unfortunately, Eric does not seem to understand. He wishes to continue comparing our results to other methods and data sets (such as NECP, ERA-40, Monaghan’s kriging method, and boreholes). We did not use those sets or methods, and we make no comment on whether analyses conducted using those sets and methods are more likely to give better results. Yet Eric insists on using such comparisons to cast doubt on our methodological criticisms of the S09 method.

While such comparisons are, indeed, important for determining what might be the true temperature history of Antarctica, they have absolutely nothing to do with the criticisms advanced in our paper. Zero. Zilch. Nada. Note how Eric has refrained from talking about those criticisms directly. I can only assume that this is because he has little to say, as the criticisms are spot-on.

Instead, what Eric would prefer to do is look at other products and say, “See! Our West Antarctic trends at Byrd Station are closer than O’Donnell’s! We were right!” While it may be a true statement that the S09 results at Byrd Station prove to be more accurate as better and better analyses are performed, if so, it was sheer luck (as I will demonstrate, yet again). The S09 analysis does not have the necessary geographic resolution nor the proper calibration method to independently demonstrate this accuracy.

I could write a chapter in the Farmer’s Almanac explaining how the global temperature will drop by 0.5 degrees by 2020 and base my analysis on the alignment of the planets and the decline in popularity of the name “Al”. If the global temperature drops by 0.5 degrees by 2020, does that validate my method – and, by extension, invalidate the criticisms against my method? Eric, apparently, would like to think so.

If he wishes to argue that our results are incorrect, that’s fine. To be quite honest, I would hope that he would do exactly that if he has independent evidence to support his views (and he does, indeed, have some). But if he wishes to defend his method, then it is time for him to begin advancing mathematically correct arguments why his method was better (or why our criticisms were not accurate). Otherwise, it is time for Eric to stop playing the carnival prognosticator’s game of using the end result to imply that an inappropriate use of information was somehow “right” because – by chance – the answer was near to the mark.

***

The second salient point relates to the evidence Eric presents that our reconstruction is less accurate. When it comes to differences between the reconstruction and ground data, Eric focuses primarily on Byrd station. While his discussion seems reasonable at first glance, it is quite misleading. Let us examine Eric’s comments on Byrd in detail.

Eric first presents a plot where he displays a trendline of 0.38 +/- 0.2 Deg C / decade (Raw data) for 1957 – 2006. He claims that this is the ground data (in annual anomalies) for Byrd station. While there is not much untrue about this statement, there is certainly a [material] [snip] omission. To see this [material omission], we only need look at the raw data from Byrd over this period:

Pay close attention to the post-2000 timeframe. Notice how the winter months are absent? Now what do we suppose might happen if we fit a trend line to this data? One might go so far as to say that the conclusion is foregone.

So . . . would Eric Steig really do this? [snip]

Trend check on the above plot: 0.38 Deg C / decade.

Hm.

By the way, the trend uncertainty when the trend is calculated this way is +/- 0.32, and, if one corrects for the serial correlation in the residuals, it jumps to +/- 0.86. But since neither of those tell the right story, I suppose the best option is to simply copy over the +/- 0.2 from the Monaghan reconstruction trend, or the uncertainty from the properly calculated trend.

When calculated properly, the 50-year Byrd trend is 0.25 +/- 0.2 (corrected for serial correlation). This is still considerably higher than the Byrd location in our reconstruction, and is very close to the trend in the S09 reconstruction. However, we’ve yet to address the fact that the pre-1980 data comes from an entirely different sensor than the post-1980 data.

Eric notes this fact, and says:

Note that caution is in order in simply splicing these together, because sensor calibration issues could means that the 1°C difference is an overestimate (or an underestimate).

He then proceeds to splice them together anyway. His justification is that there is about a 1oC difference in the raw temperatures, and then goes on to state that there is independent evidence from a talk given at the AGU conference about a borehole measurement from the West Antarctic Ice Sheet Divide. This would be quite interesting, except that the first half of the statement is completely untrue.

If you look at the raw temperatures (which was how he computed his trend, so one might assume that he would compare raw temperatures here as well), the manned Byrd station shows a mean of -27.249 Deg C. The AWS station shows a mean of -27.149 . . . or a 0.1Deg C difference. Perhaps he missed a decimal point.

However, since computing the trend using the raw data is unacceptable due to an uneven distribution of months for which data is present, computing the difference in temperature using the raw data is likewise unacceptable. The difference in temperature should be computed using anomalies to remove the annual cycle. If the calculation is done this (the proper) way, the manned Byrd station shows an average anomaly of -0.28 Deg C and the AWS station shows an average of 0.27 Deg C. This yields a difference of 0.55 Deg C . . . which is still not 1 Deg C.

Maybe he’s rounding up?

Seriously, Eric . . . are we playing horseshoes?

Of course, of this 0.55 Deg C difference, fully one-third is due to a single year (1980), which occurred 30 years ago:

Without 1980 – which occurs at the very beginning of the AWS record – the difference between the manned station anomalies and the AWS anomalies is 0.37 Deg C.

Furthermore, even if there were a 1 degree difference in the manned station and AWS values, this still doesn’t tell the story Eric wants it to.

The original Byrd station was located at 119 deg 24’ 14” W. The AWS station is located at 119 deg 32’ W. Seems like almost the same spot, right? The difference is only about 2.5 km. This is the same distance as that between McMurdo (elev. 32m) and Scott Base (elev. 20m). So if one can willy-nilly splice the Byrd station together, one would expect that the same could be done for McMurdo and Scott Base. So let’s look at the mean temperatures and trends for those two stations (both of which have nearly complete records).

McMurdo: -16.899 Deg. C (mean)

Scott Base: -19.850 Deg. C (mean)

That’s a 3 degree difference for stations at a similar elevation and a linear separation of 2.5 km . . . just like Byrd manned and Byrd AWS.

So what would the trend be if we spliced the first half of Scott Base with the second half of McMurdo?

1.05 +/- 0.19 Deg C / decade.

OMG . . . it is SO much worse than we thought!

Microclimate matters. Sensor differences matter. The fact that AWS stations are likely to show a warming bias compared to manned stations (as the distance between the sensor and the snow surface tends to decrease over time, and Antarctica shows a strong temperature gradient between the nominal 3m sensor height and the snow surface) matters. All of these are ignored by Eric, and he should know better.

Eric goes on to state that this meant we somehow used less available station data than he did:

On top of that, O’Donnell et al. do not appear to have used all of the information available from the weather stations. Byrd is actually composed of two different records, the occupied Byrd Station, which stops in 1980, and the Byrd AWS station which has episodically recorded temperatures at Byrd since then. O’Donnell et al. treat these as two independent data sets, and because their calculations (like ours) remove the mean of each record, O’Donnell et al. have removed information that might be rather important. namely, that the average temperatures in the AWS record (post 1980) are warmer — by about 1 Deg C — than the pre-1980 manned weather station record.

In reality, the situation is quite the opposite of what Eric implies. We have no a priori knowledge on how the two Byrd stations should be combined. We used the relationships between the two Byrd stations and the remainder of the Antarctic stations (with Scott Base and McMurdo – which show strong trends of 0.21 and 0.25 Deg C / decade – dominating the regression coefficients) to determine how far the two stations should be offset. By simply combining the two stations without considering how they relate to any other stations, it was Eric who threw this information away.

With this being said, combining the two station records without regard to how they relate to other stations does change our results. So if Eric could somehow justify doing so, our West Antarctic trend would increase from 0.10 Deg C / decade to 0.16 Deg C / decade, and the area of statistically significant trends would grow to cover the WAIS divide, yielding statistically significant warming over 56% (instead of 33%) of West Antarctica. However, to do so, Eric must justify why it is okay to allow RegEM to determine offsets for every other infilled point in Antarctica except Byrd, and furthermore must propose and justify a specific value for the offset. If RegEM cannot properly combine the Byrd stations via infilling missing values, then what confidence can we have that it can properly infill anything else? And if we have no confidence in RegEM’s ability to infill, then the entire S09 reconstruction – and, by extension, ours – are nothing more than mathematical artifacts.

However, to guard against this possibility (unlike S09), we used an alternative method to determine offsets as a check against RegEM (credit Jeff Id for this idea and the implementation). Rather than doing any infilling, we determined how far to offset non-overlapping stations by comparing mean temperatures between stations that were physically close, and using these relationships to provide the offsets. This method yielded patterns of temperature change that were nearly identical to the RegEM-infilled reconstructions, with a resulting West Antarctic trend of 0.12 Deg C / decade.

Lastly, Eric implies that his use of Byrd as a single station somehow makes his method more accurate. This is hardly true. Whether you use Byrd as a single station or two separate stations, the S09 answer changes by a mere 0.01 Deg C / decade in West Antarctica and 0.005 Deg C / decade at the Byrd location. The characteristic of being entirely impervious to changes in the “most critical” weather station data is a rather odd result for a method that is supposed to better utilize the station data.

Interestingly, if you pre-combine the Byrd data like Eric does and perform the reconstruction exactly like S09, the resulting infilled ground station trend at Byrd is 0.13 Deg C / Decade (fairly close to our gridded result). The S09 gridded result, however, is 0.25 Deg C / Decade – or almost double the ground station trend from their own RegEM infilling, and closer to our gridded result than to theirs.

Stranger yet, if you add a 0.1 Deg C / decade trend to the Peninsula stations, the S09 West Antarctic trend increases from 0.20 to 0.25 – with most of the increase occurring 2,500 km away from the Peninsula on the Ross Ice Shelf – the East Antarctic trend increases from 0.10 to 0.13 . . . but the Peninsula trend only increases from 0.13 to 0.15. So changes in trends at the Peninsula stations result in bigger changes in West and East Antarctica than in the Peninsula! Nor is this an artifact of retaining the satellite data (sorry, Eric, but I’m going to nip that potential arm-flailing argument in the bud). Using the modeled PCs instead of the raw PCs in the satellite era, the West trend goes from 0.16 to 0.22, East goes from 0.08 to 0.12, and the Peninsula only goes from 0.11 to 0.14.

And (nope, still not done with this game) EVEN STRANGER YET, if you add a whopping 0.5 Deg C / decade trend to Byrd (or five times what we added to the Peninsula), the S09 West Antarctic trend changes by . . . well . . . a mere 0.02 Deg C / decade, and the gridded trend at Byrd station rises massively from 0.25 to . . . well . . . 0.29. The Byrd station trend used to produce this result, however, clocks in at a rather respectable 0.75 Deg C / decade. Again, this is not an artifact of retaining the satellite data. If you use the modeled PCs, the West trend increases by 0.03 and the gridded trend at Byrd increases to only 0.26.

Now, what happens to our reconstruction if you add a 0.1 Deg C / decade trend to the Peninsula stations? Our East Antarctic trends go from 0.02 to . . . 0.02. Our West Antarctic trends go from 0.10 to 0.16, with almost all of the increase in Ellsworth Land (adjacent to the Peninsula). And the Peninsula trend goes from 0.35 to 0.45 . . . or the same 0.1 Deg C / decade we added to the Peninsula stations.

And what happens if you add a 0.5 Deg C / decade trend to Byrd? Why, the West Antarctic trend increases 160% from 0.10 to 0.26 Deg C / decade, and the gridded trend at Byrd Station increases to 0.59 Deg C / decade . . . with the East Antarctic trends increasing by a mere 0.01 and the Peninsula trends increasing by 0.03.

*** You see, Eric, the nice thing about getting the method right is that if the data changes – or more data becomes available (like, say, a better way to offset Byrd station than using the relationships to other stations), then the answer will change in response. So if someone uses our method with better data, they will get a better answer. If someone uses your method with better data, well, they will get the same answer . . . or they will get garbage. This is why I find this comment by you to be particularly ironic: ***

At some point, yes. It’s not very inspiring work, since the answer doesn’t change[indeed; your method is peculiarly robust to changes in the data it supposedly represents], but i suppose it has to get done. I had hoped O’Donnell et al. would simply get it right, and we’d be done with the ‘debate’, but unfortunately not.—eric

(emphasis and bracketed text added by me)

Eric’s claims that his reconstruction better captures the information from the station data are wholly and demonstrably false. With about 30 minutes of effort he could have proven this to himself . . . not only for his reconstruction, but also for ours. This is likely to be less time than it took him to write that post. You would think that if he felt strongly enough about something to make a public critique that he would have taken the time to verify whether any of his suppositions were correct. This is apparently not the case. On that note, I found this comment by Eric to be particularly infuriating:

If you can get their code to work properly, let me know. It’s not exactly user friendly, as it is all in one file, and it takes some work to separate the modules.

I am sick of arm-waving arguments, unsubstantiated claims, and uncalled-for snark. Did you think I wouldn’t check? I would have thought you would have learned quite the opposite from your experience reviewing our paper.

Oops.

Did I let something slip?

***

I mentioned at the beginning that I was planning to save the best for last.

I have known that Eric was, indeed, Reviewer A since early December. I knew this because I asked him. When I asked, I promised that I would keep the information in confidence, as I was merely curious if my guess that I had originally posted on tAV had been correct.

Throughout all of the questioning on Climate Audit, tAV, and Andy Revkin’s blog, I kept my mouth shut. When Dr. Thomas Crowley became interested in this, I kept my mouth shut. When Eric asked for a copy of our paper (which, of course, he already had) I kept my mouth shut. I had every intention of keeping my promise . . . and were it not for Eric’s latest post on RC, I would have continued to keep my mouth shut.

However, when someone makes a suggestion during review that we take and then later attempts to use that very same suggestion to disparage our paper, my obligation to keep my mouth shut ends.

(Note to Eric: unsubstantiated arm-waving may frustrate me, but [snip] is intolerable.)

Part of Eric’s post is spent on the choice to use individual ridge regression (iRidge) instead of TTLS for our main results. He makes the following comment:

Second, in their main reconstruction, O’Donnell et al. choose to use a routine from Tapio Schneider’s ‘RegEM’ code known as ‘iridge’ (individual ridge regression). This implementation of RegEM has the advantage of having a built-in cross validation function, which is supposed to provide a datapoint-by-datapoint optimization of the truncation parameters used in the least-squares calibrations. Yet at least two independent groups who have tested the performance of RegEM with iridge have found that it is prone to the underestimation of trends, given sparse and noisy data (e.g. Mann et al, 2007a, Mann et al., 2007b, Smerdon and Kaplan, 2007) and this is precisely why more recent work has favored the use of TTLS, rather than iridge, as the regularization method in RegEM in such situations. It is not surprising that O’Donnell et al (2010), by using iridge, do indeed appear to have dramatically underestimated long-term trends—the Byrd comparison leaves no other possible conclusion.

The first – and by far the biggest – problem that I have with this is that our original submission relied on TTLS. Eric questioned the choice of the truncation parameter, and we presented the work Nic and Jeff had done (using ridge regression, direct RLS with no infilling, and the nearest-station reconstructions) that all gave nearly identical results.

What was Eric’s recommendation during review?

My recommendation is that the editor insist that results showing the ‘mostly [sic] likely’ West Antarctic trends be shown in place of Figure 3. [the ‘most likely’ results were the ridge regression results] While the written text does acknowledge that the rate of warming in West Antarctica is probably greater than shown, it is the figures that provide the main visual ‘take home message’ that most readers will come away with. I am not suggesting here that kgnd = 5 will necessarily provide the best estimate, as I had thought was implied in the earlier version of the text. Perhaps, as the authors suggest, kgnd should not be used at all, but the results from the ‘iridge’ infilling should be used instead. . . . I recognize that these results are relatively new – since they evidently result from suggestions made in my previous review[uh, no, not really, bud . . . we’d done those months previously . . . but thanks for the vanity check] – but this is not a compelling reason to leave this ‘future work’.

(emphasis and bracketed comments added by me)

And after we replaced the TTLS versions with the iRidge versions (which were virtually identical to the TTLS ones), what was Eric’s response?

The use of the ‘iridge’ procedure makes sense to me, and I suspect it really does give the best results. But O’Donnell et al. do not address the issue with this procedure raised by Mann et al., 2008, which Steig et al. cite as being the reason for using ttls in the regem algorithm. The reason given in Mann et al., is not computational efficiency — as O’Donnell et al state — but rather a bias that results when extrapolating (‘reconstruction’) rather than infilling is done. Mann et al. are very clear that better results are obtained when the data set is first reduced by taking the first M eigenvalues. O’Donnell et al. simply ignore this earlier work. At least a couple of sentences justifying that would seem appropriate.

(emphasis added by me)

So Eric recommends that we replace our TTLS results with the ridge regression ones (which required a major rewrite of both the paper and the SI) and then agrees with us that the iRidge results are likely to be better . . . and promptly attempts to turn his own recommendation against us.

There are not enough vulgar words in the English language to properly articulate my disgust [snip].

The second infuriating aspect of this comment is that he tries to again misrepresent the Mann article to support his claim when he already knew [or ought to have known] otherwise. [snip] In the response to the Third Review, I stated:

We have two topics to discuss here. First, reducing the data set (in this case, the AVHRR data) to the first M eigenvalues is irrelevant insofar as the choice of infilling algorithm is concerned. One could just as easily infill the missing portion of the selected PCs using ridge regression as TTLS, though some modifications would need to be made to extract modeled estimates for ridge. Since S09 did not use modeled estimates anyway, this is certainly not a distinguishing characteristic.

The proper reference for this is Mann et al. (2007), not (2008). This may seem trivial, but it is important to note that the procedure in the 2008 paper specifically mentions that dimensionality reduction was not performed for the predictors, and states that dimensionality reduction was performed in past studies to guard against collinearity, not – as the reviewer states – out of any claim of improved performance in the absence of collinear predictors. Of the two algorithms – TTLS and ridge – only ridge regression incorporates an automatic check to ensure against collinearity of predictors. TTLS relies on the operator to select an appropriate truncation parameter. Therefore, this would suggest a reason to prefer ridge over TTLS, not the other way around, contrary to the implications of both the reviewer and Mann et al. (2008).

The second topic concerns the bias. The bias issue (which is also mentioned in the Mann et al. 2007 JGR paper, not the 2008 PNAS paper) is attributed to a personal communication from Dr. Lee (2006) and is not elaborated beyond mentioning that it relates to the standardization method of Mann et al. (2005). Smerdon and Kaplan (2007) showed that the standardization bias between Rutherford et al. (2005) and Mann et al. (2005) results from sensitivity due to use of precalibration data during standardization. This is only a concern for pseudoproxy studies or test data studies, as precalibration data is not available in practice (and is certainly unavailable with respect to our reconstruction and S09).

In practice, the standardization sensitivity cannot be a reason for choosing ridge over TTLS unless one has access to the very data one is trying to reconstruct. This is a separate issue from whether TTLS is more accurate than ridge, which is what the reviewer seems to be implying by the term “bias” – perhaps meaning that the ridge estimator is not a variance-unbiased estimator. While true, the TTLS estimator is not variance-unbiased either, so this interpretation does not provide a reason for selecting TTLS over ridge. It should be clear that Mann et al. (2007) was referring to the standardization bias – which, as we have pointed out, depends on precalibration data being available, and is not an indicator of which method is more accurate.

More to [what we believe to be] the reviewer’s point, though Mann et al. (2005) did show in the Supporting Information where TTLS demonstrated improved performance compared to ridge, this was by example only, and cannot therefore be considered a general result. By contrast, Christiansen et al. (2009) demonstrated worse performance for TTLS in pseudoproxy studies when stochasticity is considered – confirming that the Mann et al. (2005) result is unlikely to be a general one. Indeed, our own study shows ridge to outperform TTLS (and to significantly outperform the S09 implementation of TTLS), providing additional confirmation that any general claims of increased TTLS accuracy over ridge is rather suspect.

We therefore chose to mention the only consideration that actually applies in this case, which is computational efficiency. While the other considerations mentioned in Mann et al. (2007) are certainly interesting, discussing them is extratopical and would require much more space than a single article would allow – certainly more than a few sentences.

Note some curious changes from Eric’s review comment and his RC post. In his review comment, he refers to Mann 2008. I correct him, and let him know that the proper reference is Mann 2007. He also makes no mention of Smerdon’s paper. I do. I also took the time to explain, in excruciating detail, that the “bias” referred to in both papers is standardization bias, not variance bias in the predicted values.

So what does Eric do? Why, he changes the references to the ones I provided (notably, excluding the Christiansen paper) and proceeds to misrepresent them in exactly the same fashion that he tried during the review process! [SM Update Feb 9- Steig stated by email today that he did not see the Response to Reviewer A’s Third Review; the amendment of the incorrect reference in the Third Review to the correct references provided in the Response to the Third Review was apparently a coincidence.]

And by the way, in case anyone (including Eric) is wondering if I am the one who is misrepresenting, fear not. Nic and I contacted Jason Smerdon by email to ensure our description was accurate.

But the B.S. piles even deeper. Eric implies that the reason the Byrd trends are lower is due to variance loss associated with iRidge. He apparently did not bother to check that his reconstruction shows a 16.5% variance loss (on average) in the pre-satellite era when compared to ours. The reason for choosing the pre-satellite era is that the satellite era in S09 is entirely AVHRR data, and is thus not dependent on the regression method. We also pointed this out during the review . . . specifically with respect to the Byrd station data. Variance loss due to regularization bias has absolutely NOTHING to do with the lower West Antarctic trends in our reconstruction . . . and [snip].

This knowledge, of course, does not seem to stop him from implying the opposite.

Then Eric moves on to the TTLS reconstructions from the SI, grabs the kgnd = 6 reconstruction, and says, “See? Overfitting!” without, of course, providing any evidence that this is the case. He goes on to surmise that the reason for the overfitting is that our cross-validation procedure selected the improper number of modes to retain – yet again without providing any evidence that this is the case (other than it better matches his reconstruction).

So if Eric is right, then using kgnd = 6 should better capture the Byrd trends than kgnd = 7, right? Let’s see if that happens, shall we?

If we perform our same test as before (combining the two Byrd stations and adding a 0.5 Deg C trend, so an initial Byrd trend of 0.75 Deg C / decade), we get:

These translate into reconstruction trends at the Byrd location of 0.42 and 0.45 Deg C / decade, respectively (you can try other, more reasonable trends if you want . . . it doesn’t matter). I also note that the TTLS reconstructions do a poorer job of capturing the Byrd ground station trend than the iRidge reconstructions, which is the opposite behavior suggested by Eric (and this was noted during the review process as well).

Perhaps Eric meant that we overfit the “data rich” area of the Peninsula? Fear not, dear Reader, we also have a test for that! Let’s add our 0.1 Deg C / decade trend to the Peninsula stations, shall we, and see what results:

Weird. It looks as if the kgnd = 7 option better captures the Peninsula trend with a similar effect on the East or West trends . . . didn’t Eric say the opposite? Hm.

By the way, Eric also fails to note that the kgnd = 5 and 6 Peninsula trends, when compared to the corresponding station trends, are outside the 95% CIs for the stations. I guess that’s okay, though, since the only station that really matters in all of Antarctica is Byrd (even though his own reconstruction is entirely immune to Byrd).

As far as the other misrepresentations go in his post, I’m done with the games. These were all brought up by Eric during the review. Rather than go into detail here, I will shortly make all of the versions of our paper, the reviews, and the responses available at http://www.climateaudit.info/data/odonnell.

***

My final comment is that this is not the first time.

At the end of his post, Eric suggests that the interested Reader see his post “On Overfitting”. I suggest the interested Reader do exactly that. In fact, I suggest the interested Reader spend a good deal of time on the “On Overfitting” post to fully absorb what Eric was saying about PC retention. Following this, I suggest that the interested Reader examine my posts in that thread.

Once this is completed, the interested Reader may find Review A rather . . . well . . . interesting when the Reader comes to the part where Eric talks about PC retention.

And I love how any criticism of a peer reviewed Team paper that is posted here or at other blogs, is ripped and discredited because it is not peer-reviewed, yet, when a critique of one of our papers is not peer reviewed and posted at their blog… Well.. The world should pay attention! A bit of a double standard there, isn’t it?

Please be careful about publishing internal reviews. You should ensure that the journal’s rules allow for publication or ask permission from the editor. You did excellent work and it would be a shame to present an avenue for an attack by your detractors.

A scathing rebuttal to Steig. Any dodo, I suppose, would and will get the impression that Steig is merely trying to throw as much ____ against the wall as possible in hopes that some of it will stick. Another sad day for science. He seems like a “Doctor Jekyl and Mister Hyde” personality, as Ryan O. describes him.

I hope readers take the time to look at the detail when Ryan added trends to certain areas, it makes the case completely.

The RC guys really don’t have a clue just how much work went into this paper. When Steig said he was going to improve on it, by email I told him the methods were limited but I would be shocked if he could make any real improvement using these sorts of methods. I’ve been wrong before but I am (and I suspect my coauthors are) quite a bit more certain of that than he realizes. The RC commentary shows the limitations of the individuals critiquing the paper quite clearly IMO. Anyway, back to work.

Has anyone tried these methods on large regions well covered by weather stations? For example, by taking many stations from Scandinavia, with a few from the rest of Europe (repeating many times, with random selections), and blending in the satellite data, to see if the records from the unused stations are accurately reconstructed. Unless the method can be shown to be accurate over many Antarctica-sized regions, these detailed debates, absorbing as they may be, are moot.

Yes. I’ve done it using randomly selected stations from GHCN for the US. Take 20 or so stations, delete 30 – 70% of the data, and attempt to reconstruct. Sometimes it works well; sometimes not so much. However, as S09 accurately noted in their paper, Antarctica has a good deal more spatial coherence than the US, so a method like this is likely to perform better for Antarctica than the US.

However, as the results naturally show quite a bit of stochasticity, what one cannot answer is how close this particular result is . . . at least not without access to data that doesn’t exist.

The reason is that I was doing it for a different purpose, which required random selection. I have also done it on a smaller scale using Japan GHCN stations, though in the Japanese case, I did not combine the ground station infilling with satellite (i.e., either RSS or UAH data) to obtain a gridded result.

Wow. Excellent dissection of the trickery used here. This clearly goes far beyond anything that can be explained away by innocent misunderstanding. Not sure how Steig can respond to this except to go silent and wish it away, and that just doesn’t seem to work anymore.

Eric goes on to state that this meant we somehow used less available station data than he did:

On top of that, O’Donnell et al. do not appear to have used all of the information available from the weather stations. Byrd is actually composed of two different records, the occupied Byrd Station, which stops in 1980, and the Byrd AWS station which has episodically recorded temperatures at Byrd since then. O’Donnell et al. treat these as two independent data sets, and because their calculations (like ours) remove the mean of each record, O’Donnell et al. have removed information that might be rather important. namely, that the average temperatures in the AWS record (post 1980) are warmer — by about 1 Deg C — than the pre-1980 manned weather station record.

In reality, the situation is quite the opposite of what Eric implies. We have no a priori knowledge on how the two Byrd stations should be combined. We used the relationships between the two Byrd stations and the remainder of the Antarctic stations (with Scott Base and McMurdo – which show strong trends of 0.21 and 0.25 Deg C / decade – dominating the regression coefficients) to determine how far the two stations should be offset. By simply combining the two stations without considering how they relate to any other stations, it was Eric who threw this information away.

My understanding was that the primary TIR reconstruction in S09 used only manned station data in conjunction with the AVHRR data, and did not use the AWS data at all.

So a) Why is Steig claiming he used Byrd AWS in the TIR reconstruction, and b) why did Ryan et al use it when trying to emulate and correct S09’s TIR results? Or c) have I misunderstood what data was used for TIR?

Byrd manned station does show a strong uptrend during its life, but has no observations after 1/75, and is only spotty after 9/70. Adding Byrd AWS could be very useful despite AWS problems, but as Ryan points out, it should at least get an independent offset. However, this should be computed by something like RomanM’s PlanB regression method, rather than by subtracting out the means for unrelated periods as Steig suggests would be done.

A related question: On p. 3 of the SI, S09 admit that one big problem with AWS data is variations in height as snow builds up. (Indeed, they sometimes even get buried, as Anthony pointed out!) How is this avoided with manned stations? Do they regularly adjust the height of the shelter to offset accumulation?

I’m not entirely sure whether he used Byrd manned / AWS as a single station or if he only used Byrd manned. According to his archived READER data, he only used Byrd manned. However, given the incredibly minor differences in the reconstructions if you combine Byrd manned and AWS, I am not sure which was done. It is possible that Eric meant he didn’t use Byrd AWS at all and instead used the satellite data as a surrogate. However, if this is what he meant, then his argument is even more meaningless, as it means he simply threw away the AWS data.

I am not sure how snow buildup is avoided for manned stations, unless it is something that is routine maintenance (as I suspect). But this is a guess on my part; not a fact.

Hu
I am pretty certain that Steig did only use data from the manned Byrd station in his main reconstructions. That is what is clearly implied by the wording of his Supplementary Information, particularly when read with Table 2 thereof, which lists the Byrd manned station and AWS separately.

Steig did use Byrd AWS data for his secondary AWS temperature reconstruction, but that is quite separate from his main TIR satellite based reconstruction.

and therefore interested in, because of the nature of the game, its trend … tomorrow, next week, as well as longer term …

shadowing the Climate Scientits, and using their methods, I’m waiting for an App, in which I can fill in the monthly temperatures in Paris for the last decade, together with the number of inhabitants in Greater London, and find out what the Dow will give in a 100 years time …

It is striking to me how Team members hold everyone else in the world in contempt compared to their own (assumed) brilliance. This attitude makes them unable to appreciate being corrected and makes them oblivious to contradicting themselves.
I am again struck by the inexplicable situation of allowing Steig to be the main reviewer for a critique of his own work. Gatekeeping? Nahhhh….

I’m still ticked that they had the guts to criticize and still snip my minor replies. Now Eric left this in the thread —

[Response:Know what? I have a day job. And those guys know perfectly well I do not read those sites without a good reason to, and telling me I have ‘explaining to do’ doesn’t rise to that level. If they have scientific points to make, they should make them here.–eric]

Does anyone really think he hasn’t read this post? Perhaps we should send him a copy of the paper.

Having seen it before, I think some of these people’s behavior is consistent with “experts” who aren’t experts – they just have to bluff their way through, otherwise they fear they could lose their status.

Please be careful about publishing internal reviews. You should ensure that the journal’s rules allow for publication or ask permission from the editor. You did excellent work and it would be a shame to present an avenue for an attack by your detractors.

That could be worth checking.

However, the primary anonymity considerations are so that the referees can be frank about shortcomings when rejecting a paper, and so that the author will not feel obliged to reciprocate an acceptance when reviewing future submissions by the referee(s).

The fact that it was Steig who identified himself after acceptance suggests that perhaps pal review is the norm today in climatology.

In a comment on a previous paper like this, it would be entirely reasonable to ask the authors(s) of the first paper to write a non-anonymous review, but then that would not be anonymous, and would be evaluated differently than the supposedly impartial anonymous reviews.

I can only shake my head in awe, both at Steig’s foolish duplicity (did he really think in 2011 that it wouldn’t come out?) and at Ryan’s ability to both walk the walk and talk the talk … outstanding work, Ryan, very well done.

Pasting into R works, but you have to do step 4 as Ryan stated so that you remove any formatting problems that programs like Word introduce. Dr. Briggs did a short little series via Youtube teaching R basics and that was one of the things he brought up over and over 🙂

Ryan,
I am trying to look at this from different angles. I don’t know whether you agree.

You guys were lucky for a few reasons:
1) You got to know that Eric he was reviewer A.
2) Eric tried his trick rebuttal, out in the open

Important papers and entire careers have been ruined because people pull these types of tricks behind their adversaries’ backs in the pages of subscription journals.

Reviewing replies to one’s own papers without letting authors know, and setting up authors along argument tracks that would make rebuttals easy – if these tricks are pulled under the cover of anonymity and behind paywalls – the results can be devastating sometimes. Anyone in small fields with celebrity scientists would be familiar of this ‘nest of vipers’ effect.

The problem, however, is that the MSM and “realclimatescientists” can safely ignore anything that goes on here, because this is a “denier” site which has no relevance. Therefore they can edit away any significant replies at RC, and then say that the “deniers” have no rebuttal because it wasn’t said on RC. They’ve done it time and again.

I rarely comment, but read everything so have been following this and everything else. I say that to say this – WOW. I really thought things like this would be on the downswing after all the dirty laundry that has come to the surface regarding peer review. Now I am floored, stunned and a host of other adjectives. How can any educated person anywhere be this deliberately obtuse?

There were comments # 63 and 64 at RC that referred to my text without quoting it.
Here are the comments that were at RC. They weren’t there long, and they initially published my name and IP address, although those were quickly deleted. Making screen shots of posts on RC is a good recommendation.

#63 cagw_skeptic99 says:
7 Feb 2011 at 7:02 PM

[Edit. Resorting to threats of personal intimidation against scientists eh? Was only a matter of time frankly. Thanks for including your name in your email address.–Jim]

#64 cagw_skeptic99 says:
7 Feb 2011 at 7:33 PM

If suggesting that you will have issues testifying under oath is a threat of personal intimidation, why don’t you have the guts to publish what I said? Your house of cards is crumbling, and I am enjoying the process. You wouldn’t have perceived the suggestion that you would need to take the fifth amendment as a threat if you and your cronies weren’t quivering in your boots while waiting for your subpoenas.

cagw_skeptic99

Here is the ‘threatening’ text that they commented on, but didn’t publish, before they deleted the comments altogether:

Eric, It seems that the authors have both scientific and ethical points that have been very well made on the referenced blog posts. I am one of many who are eagerly awaiting your response, although we have no expectation that you will actually choose to do so. Your “Team” will be changing the subject, creating straw men, ducking and weaving, and hiding behind moderation on this site.
There is a pretty good chance that you and your Team will get invitations from the new House committees which investigate matters like this. I wonder if your moderation works in front of a CSPAN camera? I wonder if you will speak openly or take the fifth?

The journal _Current Anthropology_ publishes papers, critiques and responses together. It doesn’t really improve the science much in some ways, but does limit vitriol to a degree. Getting rid of anonymous review would do a great deal for science, since the reviewer has cause to be substantive and to avoid hand waving when their name is attached.

Because that’s the only way “deniers” are allowed to publish. You get one of the primary authors of the paper being rebutted as a reviewer, instead of them being required to submit a reply within the incredibly constrained way replies are allowed, just like MM were required to do.

Looking forward to their rebuttal of the rebuttal of the rebuttal of the rebuttal of S09. After following this general topic for more than a year I can’t say I’m surprised at what we see from the Team here.

As a “lay” observer of such statistical acrobatics and “my c**ks bigger than yours!”.

The Steig thing appeared as a headline cover of Nature as if it were a fact.

My understanding is however, that the Steig study used statistical methods that were so off the wall that changing obscure made up functions within the statistical analysis can lead to an entirely different outcome.

I have just skimmed all three of the reviewer a files that you have put up and am astonished at the many ploys used by Steig to delay and it also seems prevent publication of your paper. I have published in both physics and finance journals and have never seen or even heard of such shabby behavior. While his reputation for scientific ability has been knocked, his reputation for integrity is in tatters.

[Response:Know what? I have a day job. And those guys know perfectly well I do not read those sites without a good reason to, and telling me I have ‘explaining to do’ doesn’t rise to that level. If they have scientific points to make, they should make them here.–eric]

RyanO’s example here in how to analyze and detail the writing of a paper should be held up to all who might have in the past or will in the future perform such a task under the duress of being on the “wrong” side of the science. Ryan is very articulate and makes explanations that are comprehensible to the those not specialized in the area. I can, at least, partially appreciate the amount of effort he has put into his work and the defense of it. He has attempted to handle the defenses of S(09) and the impact of O(10) on S(09) with more than what I would expect in being polite and civil. I applaud him for speaking out in this thread because I must admit that at times I sometimes think: Is it just my view of a scientist or am I really seeing something that does not appear to make a whole lot of sense.

I also have much respect for the other younger authors, Jeff and Nic and their efforts in this matter as they have also helped me understand better the technical issues involved. SteveM efforts continue and he needs no kudos from me.

While I have written my opinions of S(09), and Steig, in particular, in the past, I am hoping that this thread stays on a positive note in appreciation of the effort, both technically and emotionally it takes to make the points that Ryan has here.

What impresses me the most about this effort is the amount of, what I like to call, sensitivity testing and evaluating that has been carried out in O(10) and in this thread. When as a layperson I read some of these climate science papers I can readily see where more sensitivity testing could have been applied and sometimes do it simply to satisfy myself. I think a slogan brought up by Lucia the other day is appropriate here and that is: “Where’s the beef”.

John Cooknell, I think you get it wrong and by doing so tend to trivialize the effort that it takes to carry out all the technically difficult and time consuming analyses and literature reading required to get a paper published showing the problems of a popular and acclaimed previously published paper. You make it sound like the previous paper was so bad that anyone could have pointed it out. One may instinctively see problems with a paper, but to get it down in a form that can be published and pass a rather hostile review process can be a monumental task.

While I agree mostly with your thoughtful words above, I have to say your choice of “hostile review process” is the understatement of the short year so far when we are talking about the publisher of a paper being allowed to review a paper that refutes his work. Gate Keeping is what this is. The Climategate emails hinted at it without real proof of it happening, this is the proof.

I would like to add that during the review process, we all suspected (basically knew) that it was the RC team reviewing our work. Steig, Mann and probably others. The comments matched RC comments and the tone changes in the individual reviews were strong clues. Ryan kept to his word and I was unaware that Steig had admitted to the situation until today. Dr. Broccoli (the editor) must have been under extreme pressure to fall in line, yet he simply found another reviewer and allowed the paper through.

I’m not sure the reasoning for his original decision to include Steig, but he still made the right call in the end. IMO it was a bold and strong statement that he wouldn’t allow false claims to manipulate the results. Hopefully, it doesn’t adversely affect his own funding or future. He’s shown guts in the face of a bad situation created by those playing politics.

As far as gatekeeping, IMO there was plenty of deep searching for silly reasons to stop the paper. The reviews are proof of that but I’ve seen far more egregious stuff for Steve M’s Santer rebuttal. Way way over the top.

In other words, we didn’t suffer that badly compared to what has been done and is still being done to others not included on the team.

The funny thing is, we had quite a long email discussion about including Steig as a coauthor before work became deeper. We decided it probably wouldn’t work out.

Agreed after seeing what Steve went through but even then it was from people that could feign impartiality. Steig can’t exactly do that can he? This really is the most direct example of a direct attempt at gatekeeping. From your own post – 88 pages of trying it. I too think that it was rather brave of Mr Broccoli to step up to the plate. It had to have been difficult. I do hope that Andy Revkin sees fit to set the record straight on the rather large stage he has.

But seriously, I do not think Eric is in a position to admit a significant error. Policy advocates who admit errors are ineffective. No matter how far what he says is from above board and forthright, I am sure he sees it as all justified by the ‘greater good’ of saving humanity. And that, I think, is the real lesson here: climate scientists who act as policy advocates lose scientific credibility.

He said, “Publish something or shut up”. So you published something. He tried his best to block the publication of your paper, and now he willfully distorts the results of your paper to make them appear to support the original (incorrect) Steig et al results. Ridiculous, of course, but a sad commentary on the state of ‘climate science’.

A serious question: Do Eric’s escapades as ‘reviewer A’ to block your paper, followed by his later willful misstatements, reach the level of professional misconduct? Seems to me a very close call. In any case, he should be ashamed of himself.

I do not think Steig was ever attempting to “block” publication of the paper. I also think that when he said that he thought the paper overall contributed to the discussion that he was being honest.

Rather, what I feel he was trying to do is control the message by requesting editorial changes that could be interpreted later in multiple ways. I’m as yet undecided if this was intentional, or if his paper was simply so personally important to him that he could not see what he was doing. He’s human, after all.

The most difficult thing to reconcile in all of this is the difference between Eric Steig in emails (professional, friendly, helpful, and honest) and Eric Steig at RC (snarky, pompous, and condescending). Perhaps he played me for a fool – though I doubt it – but I think the former is closer to Eric Steig’s true persona than the latter.

I’ve read many of his papers, and I’ve found them to be well-written and entirely plausible (though parts of most are above my head). If all you had from Eric Steig were his past papers and his emails between Jeff Id and myself, you would have a very different impression of him than what you have now. Even so, there is only so much of Eric’s public misstatements that I will tolerate before I go off-shift.

However, I think this is best resolved here – in the open – than what I think you are implying. Bad judgment? Sure. Dishonest tactics? You bet. Professional misconduct (where, I am assuming, the implication is that some sort of official action should be taken)? No, I don’t wish that.

I perhaps lean more toward the theory of ‘walks like a duck’ than you do. I am not privy to the personal correspondence, of course, and perhaps that would be persuasive in his favor. But the series of review comments (I read them all this evening) from reviewer A can be most generously be seen as shamelessly self serving, and I think, more honestly can be seen as an outright and willful effort to obscure and/or delay revelation of the clear methodology errors that O10 showed were present in S09. Had he repeated even one more time how your paper *had* to say that it confirmed S09, I would probably have vomited. Were I Steig’s provost, I would never let this one slide. Good for him I guess that I am not.

“The most difficult thing to reconcile in all of this is the difference between Eric Steig in emails (professional, friendly, helpful, and honest) and Eric Steig at RC (snarky, pompous, and condescending).”

My opinion is that RC is the PR firm managed blog that protects the money that flows to the Team in the form of grants, and the source of MSM publicity that does the same. A Team member is subject to the rules of the game on the web site when Team members and the PR managers are watching. Private conversations are subject to different rules, but maybe not so much going forward.

The Team simply cannot afford to have anyone stray from the message. Any admission of error could be the one that pulls down the whole house of cards. I read that over $500K was spent protecting Dr. Mann’s emails at U VA. Why and who would come up with that kind of money? It will only take one person with insider knowledge and maybe a few more emails to seriously damage the credibility and reputations of the whole Team. Likely their professional reputations will never recover.

Re: Ryan O’Donnell (Feb 7 20:10),
Ryan O,
The situation must be doubly upsetting to you (and Jeff and Nic). The two-facedness of the seemingly cordial and cooperative correspondence contrasted with the obstructive review process. The Stieg comment in Steve McIntyre’s comment above shows the man is quite comfortable with deception and in this case it would appear to be needless deception. I recall reading that particular Stieg post and thinking how nice it would be, based on the tone of Stieg’s post,if there could be some reproachment between the factions. I did not dream that Stieg might have actually been a reviewer. But the sin at the root of all this is Stieg accepting the role as reviewer A. Plainly and simply, it was a conflict of interest and an homourable man would not consider acting in such a capacity.

I think Steig can certainly participate, but he should have put his name on the reviewer comments starting from the first. Everybody (including O’Donnell et al) deserved to know who was making these comments. A honorable person would also acknowledge at the start of his first comment the obvious conflict of interest, and ask the journal editor to consider this conflict in weighing his review. What is to me most disturbing is that Steig seems so lacking of self awareness. How does one reach his age and position with so little self awareness? I do not know. Does he really think he is beyond normal human temptations and failings? His actions suggest he does.

There is another confounding influence for the temperature measurements at Bryd station that might not be widely appreciated. The local terrain has not been stable over the years. Bryd station, which was originally flat now has a substantial hill.

Antarctica is generally flat but any semi-permanent obstruction to the near constant wind creates an up wind as well as a down wind snow drift. Eventually the obstruction is buried.

The camp at Bryd station has been buried and rebuilt multiple times, each time more or less on top of the older buried structures. The ice runway a few hundred yards away – as far as I know- is at the “original” altitude but the Semi-permanent Korean war era Jamesway shelter is at the summat of a substantial hill.

An ice core drilling rig – looks like a small oil drilling rig- is about 3/4 buried.

The hill might not be high enough to make a difference in terms of local atmospheric lapse rate but it does cause local atmospheric effects.

A number years ago I had the experience of
standing near the base of the Bryd station hill facing into the wind. There was a substantial Ice fog at the level of the ice runway but the wind driven fog dissipated into thin air over a distance of 10-20 yards as it impinged upon the gentle rise.

I was standing just above a seemingly endless sea of wind driven fog which continuously disappeared just a few feet upwind from where I was standing.

Was this a temperature effect? a pressure effect? or something else? I have no idea.

It seems to me even a small hill could have a profound effect when the sun is low on the horizon, significantly increasing solar radiation on the surface on the sun ward side and creating a very large shadow on the anti-sun ward side.

Furthermore to be fair I have no idea exactly where the temperature measurements where made. If they where made near to the camp itself I expect the changing terrain would have some sort of long term effect. If they where made on the mostly stable ice

Are these terrain related confounding effects make any difference to the analysis.

This is amazing. A paper that said based on our made up stuff, there is a definite possibility of antarctic warming, which turned into a paper that said there is a possibility of warming (After Hu noted an error on how confident they could be about their made up stuff), to a paper that said the Antarctic doesn’t really seem to be warming but there is a chance according to our made up stuff, to their paper proves that there is a chance that the Antarctic warming proven in our paper may be right, to the data they made up is not as good as the data we made up, to they made up stuff to keep us from publishing our made up stuff, proving he didn’t know how to make up stuff.

I would need to see the text before and after to make any judgment. I have run the code (many times, I might add) in a clean R session and not had any issues. So have several others, some of whom tried it for the first time today.

I am completely out of my depth in threads of this type. I would just suggest that anyone commenting on the technical aspects of the dispute actually cite the literature being critiqued rather than use shorthand in referring to those articles, otherwise those critiques will never show up in search results for interested people who are using the citations (or even partials such as author names, or date and subject and maybe journal) as search terms.

flogging a dead horse me thinks… for example recent Jan storms attributed to AGW when in fact Jan temps AMSU satellite temps showing -0,01C please get a life….Are you scientists or not? bothering to deal (this posting) with these cranks Steig et al…at least I published 27 statistical papers in refereed journals… its becoming a joke and not worth anymore of my time,. that is agw or anti agw chao

When Ryan announced the acceptance of O’Donnell et al 2010, Steig posted the following comment at Jeff Id’s on December 2, 2010 – a comment that bears re-reading given that Steig was Reviewer A and had done everything within his power to delay and block publication of O’Donnell et al 2010:

Back when Ryan O had written comments at RC, I said something like “I encourage you to submit this work for publication.” I’d glad to see that this work has gone through the peer review process, and I look forward to reading it.

I appreciate also Ryan’s comment that “I would hope that our paper is not seen as a repudiation of Steig’s results, but rather as an improvement” and his emphasizing that their results (evidently) back up our most important point – -the significant warming West Antarctica.

This is indeed the way things ought to work — and evidently do. Too bad Steve McI seems bent on spinning it otherwise. His claim that this new work ‘refutes’ mine is a prime example of why I cannot take him seriously.

Ryan, if you don’t mind sending me a preprint, and a link to your reconstructed data, I’d appreciate it.

I will presumably have more to say after I get a chance to read the paper, but it’ll be a month or more as I’m simply too busy with current projects.

Lucia covers this point here, calling Steig the Rod Blagojevich of science (perhaps of Nature?).

Just to extend the pattern, I’ve got some nice emails telling me the code – which at RC did’t exist – was too messy to present. He’s so nice by email, I almost offered to clean it up for him and release it when he was satisfied. After the comment and peanut gallery reaction at RC about all the code being available, it would have been pretty easy to run him over in blogland for that. This really never was about the people involved, just the math. The wall-to-wall behavior is turning it into a people story.

While Eric complains that Ryan’s turnkey code is too difficult to copy paste and run, we still don’t have Eric’s code. Not that we want it anymore.

Is not it more important to stay on message with what RyanO has done here in his analysis with loads of sensitivity tests than get into a pis-ing contest with Steig and his loyalists about whether his work should be retracted or he should be professionally reprimanded. All that does is change the subject.

I would submit that he has used duplicity as RyanO shows here and I think personally with his lack of the use of sensitivity tests in his own defense, he might be a bit lazy or at least not the hard-nosed worker that Ryan O shows to be.

As merely a guy who likes old light bulbs who has been following Tom Nelson’s climate news blog as part of my daily reading, mainly for fun, as a sociological study in how news stories propagate, ha ha here and oh boy oh boy there, but this story, seemingly so obscure and nuanced amounts to this: the most important mainstream peer reviewed journal, a primary literature journal of the highest order, published a cover story that was the work of a data magician rather than a classic old world self-disciplined scientist. This is a so sad.

After getting a Ph.D. at Columbia and doing a postdoc at Harvard in chemistry and then nanofabrication, I started my own small fabrication (of art, no less) company instead of pursuing an academic post. Why? Back then, a decade ago, it was because science had lost its young role models. It had suddenly become all about “well what is going to be the pay off of your research?” rather than “why is that interesting?” Suddenly it was all about drug delivery vehicles and faster desktop computers instead of figuring out first principles or general creative methods of doing things.

Boom, a decade later, it’s all applied science. Political science, that is.

Comments on this topic at RC appear to have been closed – last one is *63. When this happened before it seemed to me that all the major players at RC got together to review the offending piece and settle on a going forward policy. I suspect they are all reading through Ryan’s piece and figuring out how to salvage Steig. I expect Gavin to step forward and take the heat – or at least that is what has happened before.

Given past reading of Australian Antarctic stations shifts and reasons, I suspected that shifts at Byrd might be a problem. I do not have the coordinates of the various weather recording devices, but there are accounts of the movements of the buildings at, for example, http://antarcticsun.usap.gov/features/contentHandler.cfm?id=1794 If the instruments were moved with each main building move, the story becomes even more complicated.

I have zero experience with R programming. I downloaded and installed the R runtime from the link above and followed the instructions to run the program. It took a while – probably close to 45 minutes or so on my 4GB Core i5 laptop running Windows 7 64-bit – to run but it did run perfectly, no errors. It’s cool how it downloads the data for your automatically.

If I can do it then anyone with a capable machine and Internet access should be able to do it.

And for not the first time, the suggestion that the cover of a future “Nature” be decorated with “Ryan’s Tiles”, so that the corrective O10 paper therein gains prominence. There are strong reasons why the material at the head of this post are more important to the Philosophy of Science than the original S09 paper that scored the cover in 2009, but showed a probable over-estimate of warming.

(Ryan’s Tiles are a selection of boxes that show how the Antarctic temperature analysis depends on selected statistical parameters that can be varied. A large part of the O10 response deals with clever ways to identify the most judicious selection of those parameters. I made a poor mock-up a year ago http://www.geoffstuff.com/Ryan%27s%20tiles.jpg ).

Research Misconduct—Research misconduct is fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. Research misconduct does not include honest error or differences of opinion. A finding of research misconduct requires that:

* There be a significant departure from accepted practices of the relevant research community; and

* The misconduct be committed intentionally, or knowingly, or recklessly; and

* The allegation be proven by a preponderance of evidence.

Research misconduct is a form of scientific and scholarly misconduct identified as an inappropriate activity in the Faculty Code, Chapter 25, Section 25-51.

A faculty member having tenure under the provisions of this chapter may be removed for cause from his or her position or subjected to reduction of salary only for one or more of the following reasons:
A. Incompetence.

E. Scientific and scholarly misconduct, consisting of intentional misrepresentation of credentials, falsification of data, plagiarism, abuse of confidentiality, or deliberate violation of regulations applicable to research (see Executive Order No. 61).

F. Conviction of a felony.

G. Intentional and malicious interference with the scientific, scholarly, and academic activities of others. To warrant a removal for cause or reduction of salary, conduct falling within these categories must in a substantial way adversely affect the faculty member’s or the victim’s academic, scholarly, or professional ability to carry out his or her University responsibilities.

Go get him. They will argue that only section E applies and not section G.

So, after all Steig’s apparent moral high ground talk about rising above the snark and engaging with sceptics he considered to be polite, we get this. Steig has reverted to type and the standard team tactics. My current team recipe looks something like this:

1. Come up with an ad hoc statistical methodology involving a series of processes, such that there is complex interaction between them which is largely unknown in the statistical literature. The resulting algorithm should be highly sensitive to, and give different results for parameter / data changes that really shouldn’t matter and that most reviewers wouldn’t look too hard at.

2. Play with your complex model and data, tweaking things when you “accidentally” “stumble” across a result that matches the consensus view well, but somehow offers a “new insight” over previous results. Publish.

3. Some meddling kid sceptic publishes a rebuttal, pointing out your methodology is seriously flawed, and when you change parameter A (to which a good result should be insensitive), the new insight conclusion no longer holds, showing the methodology cannot be used to support the original claim.

4. Publish a rebuttal on a blog that shows even if you do change parameter A and end up with a completely different answer, subsequently changing another seemingly unimportant parameter B after changing parameter A gets the original result back. Act as if the sceptic’s paper was not an attempt to show the methodology was flawed, but as if the sceptic was claiming their result was somehow better. Ignore the fact that you are now openly tuning your non-robust sui generis methodology to get the answer you first thought of. “Prove” that your own result is better by a posteriori selection of some esoteric measure is better for your result than that of the sceptics.

5. Preen while political advocates heap praise upon you in the comments on your blog. Delete any sceptic comments. Continue to preen as any enquiries spend a lot of money to carefully look in the wrong direction and find no problems. Viciously attack (with the help of your advocates) any academic that steps out of line.

6. ???

7. Profit.

This was supposed to be an overview of the McIntyre vs. Mann case but looks like it will fit O’Donnell vs. Steig pretty well too. Steig is now about half way through 5.

In his latest RealClimate post, Steig now admits that he is not a statistician. Hmm, now why does that sound familiar?!

Newsflash to team: you don’t have to be a statistician to do science, but it does help if you at least understand the properties of the statistical methods you are using. And when I say “does help”, I mean “is pretty fundamental to the job you are doing”.

To be perfectly honest, I’m really intrigued how they are going to try to wriggle out of this one. I’m betting they are paying big money for damage control advice right now in one of their “war councils” and it likely be a wonderful lesson in creative writing within a framework of an alternate universe.

I had asked at RealClimate why not have a blogroll link in other opinions, to Climate Audit, Peilke Jnr and Lucia’s Blackboard, as an example of goodwill

[Response: Being listed on our blogroll does not constitute endorsement. In general, the sites we do list — whether they are run by scientists or not — tend to get the science right much of the time, and hence are consistent with our mission. Being not-listed could mean that

a) we haven’t heard of the site,
b) that it is uninteresting or unimportant, or
c) that we consider it dishonest or disingenuous with respect to the science.

Pielke Jr, Blackboard, and ClimateAudit all fall squarely into the latter category.–eric]

“Didn’t Eric say their reconstruction better captures the ground station data from Byrd?”

Eric did not state that explicitly, but he does mention that you reconstructed a temperature trend for Byrd which is +0.08 C/decade, while for example the Monaghan et al 2008 reconstruction for Byrd comes out at +0.32 C/decade, and the updated Monaghan estimate indicates an even higher trend (> 0.4 C/decade).

These are a very significant difference in trends, and one may wonder (1) how you validate such a low trend for Byrd, and (2) why you do not explain the difference between the Monaghan trend and your in this post, and (3) why you attack Eric for bringing such differences in trends at Byrd to the readers attention.

The current posting indicates that the O10 paper was not abut proposing an accurate reconstruction of Antarctic temperatures. Rather it was to show that the Steig paper was mathematically flawed. The posting demonstrates this by showing some sensitivity tests that indicate that the Steig method will show anomalous trends outside of the peninsula if temperatures within the peninsula are artificially increased. The Steig method spreads the warming within the peninsula across the rest of Antarctica. O10 corrected these mathematical errors and showed a corrected method that did not create these spreading artefacts. What O10 did not propose was that even the corrected Steig method would produce an accurate reconstruction.

Eric’s post depends on being able to treat Byrd as a single station. His method of combining the stations is arbitrary, and does not work elsewhere in Antarctica (i.e., Scott and McMurdo). Until Eric can provide a better offset and justify the offset and explain why RegEM can find the “correct” offsets for other stations (but not Byrd), his argument is moot.

One thing I did for the paper was to spend several days worth of time comparing the trends of the TTLS recons to the trends of the simple method. That was what I was most concerned with. I don’t recall ever sending emails on my results to anyone else in our group but I was satisfied that the iterations of the method were creating the offsets in a reasonable fashion. IMO the convergence to offset anomaly data was one of the cooler bits of the code’s operation. EM is pretty neat.

Ryan, thank you for your response.
Maybe you misunderstood my inquiry.
I point out that the rate of warming you reconstructed for the Byrd turned out to be +0.08 C/decade, while the raw data (with zero offset) and Monaghan reconstruction suggest a warming trend of some +0.32 C/decade.

Without an explanation of the factor 4 inconsistency in findings between your paper and Monaghan, how are we to know if your statistical methods are a more realistic assessment of the temperature changes at Byrd (or anywhere else) over the past 50 year than Monaghan ?

So can you please explain how exactly you obtained the +0.08 C/decade rate at Byrd ?

For starters, I understand that you calculated an offset between the Byrd manual station and the Byrd AWS station. If so, can you please share with us what that offset came out to be ?

The relevant question here is not how the “findings” compare at an individual station point of the reconstructions. This is a straw man. The relevant question is: how do the respective methods of OLMC10 and S09 utilize the station data? Ryan has shown how S09 utilizes the station data, and S09 reconstructed Byrd is shown to be an artifact of spurious correlations with the oversampled peninsula. Therefore any S09 “findings” at Byrd are meaningless.

As for the suggestion that AWS and surface station data should be spliced based on an Steig’s post, I’m with Ryan. Until a physical justification for a straight splice (which overrides the relationships amongst AWS, manned, and surrounding data points) it is a non starter.

In absense of an answer to my question, let me make the issue a bit clearer.
Byrd is not just “an individual station”, it is the ONLY station on West Antarctica that has a temperature record before 1980.
Any reconstruction that does not match the Byrd station data at least somewhat realistically is thus useless and should be discarded as statistical unsound at the earliest convenience.

Ryan mentions in his post above mentions that “the 50-year Byrd trend is 0.25 +/- 0.2 (corrected for serial correlation)” which confirms assessments done by Monaghan. However, the statistical methods and parameters chosen in O10 result in a trend of +0.08 C/decade for the full Byrd record. Why ? Because
the statistical methods and choice of parameters used by Ryan calculated an ‘offset’ between the manned (before 1980) and the automatic (after 1980) stations. Why an offset ? Because the considered them as ‘individual’ stations. Why not consider the fact that they eprisent a single location because they are only 2.5 km apart ? Because Ryan above claims that “microclimates matter”. If anyone has ever been to Byrd, or has seen the pictures on Google Earth, it would be very hard to validate ANY offset between two stations being 2.5 km apart on that deserted ice field without a proper explanation.

Instead of assuming an offset of 0 (the null hypothesis), Ryan calculates the offset based mainly on “regression coefficients” of two stations located more than 1000 miles away, on the East Antarctic coast (Scott Base and McMurdo). And then again, Ryan avoids mentioning HOW MUCH the offset at Byrd actually turned out to be with his statistical methods.

Now does this offset at Byrd matter for the final conclusions of the paper ? Ryan states “what happens if you add a 0.5 Deg C / decade trend to Byrd? Why, the West Antarctic trend increases 160% from 0.10 to 0.26 Deg C / decade”. In reality, the only trend that his unsubstantiated offset created is a 0.25 – 0.08 = 0.17 C/decade, which would increase the trend from West Antarctica in the O’Donnell from 0.1 to some 0.15 C/decade. With uncertainty margins, this would bring the O’Donnell ’10 conclusions very much in line with the Steig ’09 reconstruction that it is trying to ‘correct’.

“Any reconstruction that does match the Byrd station data at least somewhat realistically is thus useless and should be discarded as statistically unsound.”

Except that the “Byrd station data” does not give an unambiguous answer on its own, due to the sensor change and tons of missing data.

“Why not consider the fact that they represent a single location because they are only 2.5 km apart ? Because Ryan above claims that ‘microclimates matter’. If anyone has ever been to Byrd, or has seen the pictures on Google Earth, it would be very hard to validate ANY offset between two stations being 2.5 km apart on that deserted ice field without a proper explanation.”

Right after “microclimate matters” in Ryan’s post, we have a pretty good explanation of the reasons for not considering them one station:

“Sensor differences matter. The fact that AWS stations are likely to show a warming bias compared to manned stations (as the distance between the sensor and the snow surface tends to decrease over time, and Antarctica shows a strong temperature gradient between the nominal 3m sensor height and the snow surface) matters.” So these are different sensor types, manned vs. unmanned, at different heights…I would say that given this, the burden of proof is on those who claim these COULD be considered one station, especially since you are discarding two other statistical methodologies for determining the offsets.

Furthermore, Ryan provides an example that shows that McMurdo and Scott Base, which are also 2.5 km apart, give physically unrealistic results when spliced together.

Now, there is the point that an independent Monaghan reconstruction shows a higher trend for Byrd. I have not read the whole 2008 paper, but in a quick skim of it at http://polarmet.osu.edu/PolarMet/PMGFulldocs/monaghan_bromwich_jgr_2008.pdf the Figure 14 does NOT seem to show a trend for 1960-2005 Byrd? Nonetheless, assuming that I’ve misread this (fairly likely), and that Monaghan indeed estimates a higher trend at Byrd and has valid reasons for arriving at this estimate, we arrive at the conclusion that RegEM cannot find the “correct” offsets for this station.

We’re thus left wondering, as Ryan brings up, how RegEM can find the correct offsets for other stations, but not so for Byrd. If it cannot, both the O10 AND S09 reconstructions are, as you say, “statistically unsound”.

The fact that O’Donnell considered Byrd to be two stations is not the problem. The problem is how they calculated the ‘offset’. O’Donnel states :

“We used the relationships between the two Byrd stations and the remainder of the Antarctic stations (with Scott Base and McMurdo – which show strong trends of 0.21 and 0.25 Deg C / decade – dominating the regression coefficients) to determine how far the two stations should be offset.”

So they used a statistical method to calculate the ‘offset’, which is based on stations a 1000 miles away in a completely different setting (coastal hills) and a different part of the continent.

Then, when (not surprisingly) they obtain a significant offset, they try to validate that by handwaving at microclimates and sensor differences. That is ‘putting the horse behind the wagon’ at best and scientifically dishonest at worst.

Also, you cannot use the excuse that RegEM works fine for ‘other stations’ because these other stations are mostly on the Peninsula, much closer to each other and have very complete and overlapping records and thus are have strong correlation records.

Besides all this, the thing that is really disturbing is that O’Donnell avoids even stating what the ‘offset’ between the two Byrd stations actually turned out to be with their methods. Why not simply state that, so we can all argue if that offset is reasonable or not ?

I’m sure we can get this number (probably in the range of some 0.6 C) can be obtained from JeffId’s code easily, but I am not enough familiar with R to get that number out.

Re: Rob (Feb 13 05:29),
Clearly, sensors 2.5km apart can vary quite significantly. A friend manages sensors at various locations on our local airport property (COS.) He reports up to six degree variations all within one mile. And that’s on one piece of flat mostly-treeless property, out in the open.

I don’t know why people are astonished at the idea of using far-away spaced-sensor-stations to help analyze the potential for variation between a given set of two sensors.

Isn’t the real problem simply that there is hardly any data? So everyone is truly guessing about the data. Thus, the challenge is to discover what analysis methods are mathematically correct or incorrect. Nobody can “prove” something about data that we don’t have.

Seems to me that learning about variability from other examples is quite reasonable! But then, what do I know.

WHY would it be “scientifically dishonest,” let alone “putting the horse behind the wagon?” Seems obvious that two locations will likely have some variability. Please show us why Ryan’s method is invalid, and/or show us a provably better method!

(BTW, that’s an interesting variation on “putting the cart before the horse” 🙂 )

MrPete wrote “WHY would it be “scientifically dishonest,” let alone “putting the horse behind the wagon?” Seems obvious that two locations will likely have some variability.

The two Byrd stations could have a bias (one consistently higher or lower than the other) in which calculating an offset is valid. For example, O’Donnell states that Byrd AWS is mounted at 3 meter altitude and Byrd manned apparently not. An offset between them could be defined based on that difference in altitude, with some physical reasoning. That would be scientifically completely acceptable.

But O’Donnell did not do that. Instead, they used their own statistics (based on stations 1000 miles away in a completely different environment) to obtain an offset number and then tried to find the physical reasons that the number my be correct after the fact.

That is what I call “putting the horse behind the wagon”, and is scientifically dihonest, since he allows (offsite, somewhat arbitrary) statistics to determine physics at the Byrd location.

At the very minimum, O’Donnell should have shown the result of his statistical methods when considering Byrd to be one station (just like everyone else did), or with offset 0 between the stations (which has the same effect as considering them a single station).

The fact that O’Donnell considered Byrd to be two stations is not the problem. The problem is how they calculated the ‘offset’. O’Donnel states :

“We used the relationships between the two Byrd stations and the remainder of the Antarctic stations (with Scott Base and McMurdo – which show strong trends of 0.21 and 0.25 Deg C / decade – dominating the regression coefficients) to determine how far the two stations should be offset.”

So they used a statistical method to calculate the ‘offset’, which is based on stations a 1000 miles away in a completely different setting (coastal hills) and a different part of the continent.

From, Monaghan (2008) regarding Byrd:

The station and passive microwave records were combined into one record, and then the remaining missing data were filled in by optimizing the multiple linear regression relationship between the Byrd Station temperature record and records from other Antarctic stations for each month, and for the annual means.

So, it’s OK for Monaghan, but not for O’donnell?

Assuming that no offset would be necessary for proper comparison and just using the two sequences as is would be blatantly naive. Since the two records do not overlap, calculating anomalies on the same time period is not possible. Furthermore, there are practical considerations due to other factore such as “Byrd does not have year-round manned records after 1969, although there are scattered summer observations through January 1975” (Monaghan 2008). These can cause substantial differences in the patterns for different seasons, Thus, it would be more to the point to calculate (possibly different) offsets for each month when putting the two records on the same basis. Finding the “optimum” 😉 method for doing this is a different issue.

“The fact that O’Donnell considered Byrd to be two stations is not the problem. The problem is how they calculated the ‘offset’”

So, we agree that treating them as one station does not make much sense, given all the issues explained above. Perhaps we can also agree then that there is no unambiguous picture of the trend for this station/stations, and instead depends upon the method for calculating the offset. You consider there to be a “problem” with R10’s method, which is fine. However, I hope you also see that simply assuming “0” for this offset without using any method is arbitrary. Or at least that if trends can vary wildly between Monaghan 2008 and that of the updated, unpublished Byrd data, perhaps relying on this single, data-challenged station to invalidate an entire reconstruction may be a bit premature? And that maybe the statement “Any reconstruction that does not match the Byrd station data at least somewhat realistically is thus useless and should be discarded as statistical unsound at the earliest convenience” must be qualified by the fact that there is a whole lot of uncertainty surrounding Byrd…

P.S. If I get a chance, I’ll try fiddling with the code to see if I can figure out the number used for the offset.

Troyca wrote “So, we agree that treating them as one station does not make much sense, given all the issues explained above.”

On the contrary. None of the ‘issues’ described above relate to the ‘offset’ between the two Byrd stations. An ‘offset’ between two stations 2.5 km away is only allowed if there is physical evidence that that offset even exists. That could be evidence obtained by overlapping records (which unfortunately is not the case at Byrd) or could be because of some physical effect (difference in altitude or known bias in sensors). Heck, if O’Donnell wants to validate the offset by claiming an urban heat island effect in the manned AWS station because Byrd-manned is close to the Byrd airstrip, then that is fine and we can argue about the effect of that airstrip. But statistics from 1000 miles away are NOT a reason to assume a non-zero offset. Statistics should not become a reason by themselves.

O’Donnell’s statistics may be better than Steig’s (and Steig actually admits that), but
that does not give them the right to use these statistics where they definitely do not apply.

Offset 0 is not ‘arbitrary’ as you suggest. It is the ‘null-hypothesis’, and any non-zero offset would need to be estimated by physics and reasoning and not correlation statistics from a 1000 miles away.

I hope that you can find the offset that O’Donnell calculated between the two Byrd stations. O’Donnel himself reports +0.25 C/decade for Byrd for zero offset, while after the offset is applied this reduces to +0.08 C. That means that the offset must have been something like 0.6 C or so, but it would be great to see the actual number.

Either way, it would also be great to see what would be the result of O’Donnell’s statistical methods if they considered Byrd to be a single station (just like all other researchers did).

Ryan has given you an example of stations under similar conditions that give ridiculous results when spliced together with no offset. You can find plenty of other station moves (many less than 2.5 km) in the USHCN that result in step changes, which the PHA then corrects for using correlation statistics to produce the F52 dataset. Indeed, these seem to be pretty convincing reasons to believe there is at least SOME difference caused by the (or any) station move.

Now, you claim that “statistics should not become a reason by themselves,”, but I suspect you okay it in other offset calculations with RegEM and in the PHA, correct? And that, indeed, in this case you merely object because of the “1000 mile” distance of the nearest stations?

Well, that’s fine. O10 has employed 2 methods to calculate the offset using what data is available, but you may say that these methods aren’t accurate because of the distance. You can even throw your hands in the air, claim there isn’t enough data, and that we might as well just assume an offset of 0 (your “null hypothesis”) because heck, we can’t prove with 95% certainty that it isn’t 0. All of that is fine. But how can you possibly turn around and take this one default value with enough certainty to claim that we should throw out any reconstruction that doesn’t match this resulting station trend?

You quote Monaghan 08, “Because portions of the Byrd record have been reconstructed, the…temperature trends may be viewed with skepticism.”

Now, in the above I’ve removed “negative”. Do we suddenly remove this skepticism of the updated and unpublished result simply because it now reads “positive”?

I wouldn’t argue that O10 definitely got the right trend for Byrd. But just as Steig 09 wasn’t thrown out over its disagreement with Monaghan 08 regarding an uncertain Byrd trend, I don’t think O10 is “statistically unsound” because of some ambiguous station data at Byrd.

We do not explicitly calculate offsets. We use RegEM to regress the actual station data to estimate the missing station data. As the overall mean for each station is subsequently calculated using the actual data + estimated data, this regression results in a change in mean for the actual data. This process continues until the numbers stop changing.

To say that we calculated an “offset” for Byrd implies that we did something special with respect to Byrd. We did not. In fact, this same concept of “offset” applies to every single station used during the infilling. Offsets result for every station, not just Byrd. In fact, the continental trend is almost entirely the result of this offsetting process (which is nothing more than an update to the series mean). Without the updates to the means, the continental trend would be near zero.

My argument is simple: If RegEM cannot be trusted to obtain the right offset for Byrd, then how can it be trusted to obtain the right offset for anything? Byrd is not treated any differently than any other station in the algorithm, so if it gets Byrd wrong by ~0.3 degrees or so, then the entire reconstruction is junk.

(Since you asked, the average mean update to the manned Byrd station is -0.05 and the mean update to the AWS station is +0.07, yielding a +0.12 offset for the AWS station compared to the manned station when they are considered as independent records.)

This was my point to Eric. If he claims that RegEM got it wrong at Byrd by such a significant amount, then he is tacitly admitting that it easily could have gotten it wrong everywhere else by a comparable amount. Given the magnitude of the trends present in the raw station data, if the error in the RegEM estimates of the means is anywhere approaching what Eric claims must be true for Byrd, the calculated trends are almost entirely mathematical artifacts.

However, we do spend a good deal of time checking whether RegEM got it right. To obtain the verification statistics, each station is withheld, one at a time, from RegEM. The reconstruction is performed without that station. We then compare the estimated values back to the original station values.

We also conducted the same test using the S09 reconstruction . . . i.e., withhold each station one at a time, perform the reconstruction, and compare the estimated values back to the original station values.

FOR EVERY SINGLE STATION used by both us and S09, our reconstruction shows significant improvement over the S09 reconstruction. In fact, our reconstruction – with the station entirely removed from the calculation – explains more variance and shows less of a mean bias than the raw AVHRR data. In other words, our reconstruction does a better job of reproducing both the variance and mean of the station data than the satellite measurements – even when that particular station is not used at all in the reconstruction.

So is it possible that our “offset” for Byrd is wrong? Sure. There’s a lot of uncertainty with any regression method on sparse data. That uncertainty is unavoidable. But based on withholding tests, it is far more statistically likely that our results are closer to the truth – assuming the underlying station data is correct and that the covariance structure of the satellite data is a good proxy for the covariance structure of near-surface air temperature measurements.

Lastly, I notice that you have never asked what the “offset” is for S09.

If you are curious, the “offset” for S09 (they don’t use the AWS station at all, but one can still compare means for the infilled manned station series) is approximately +0.15.

The infilled trend at Byrd (i.e., the station data with the missing values estimates) in S09 is +0.13 deg C / decade.

The gridded reconstruction trend at the Byrd location, however, is double that . . . clocking in at 0.26 deg C / decade.

Note how the infilled station trend in S09‘s reconstruction is much closer to ours than their own gridded trend. Why is this? Because the choice of using only 3 AVHRR PC’s adds in more than a bit of Peninsula warmth.

I re-read your post many times, digged through the R code, and finally concluded that there are some things about the statistical methods and/or the terminology that I do not understand yet. Rather than bother you and other posters here any further with assertions that may be irrelevant, I will do some more research first. I apologize if I made statements that made no sense.

Maybe the best way to summarize my concern with your reconstruction is that it is not clear how sensitive your method is to decisions between considering Byrd ONE station or TWO, and how that decision would change the conclusions of your paper.

Now, you have made it abundantly clear that you believe that your method is superiur to Steigs, and Steig does not deny that.

But also, with all due respect, you have not been clear on how the results of your reconstruction would change if you would consider Byrd one single station. After all, one need to consider that the guys taking measurements back in the 50’s and 60’s did read the thermometer correctly, and that the readings from Byrd AWS are also correct. What would happen if we would give these readings the benefit of doubt, and accept them as if they came from the same physical station, rather than from two different sources as you assume ?

I just started playing with your R code, to see if I could find the answer to that question myself, but if you already did that excesize, I would be most interested to know the result.

Besides that, I would like to congratulate you and your co-authors with your publication in the Journal of Climate. I know how much work there is involved in getting substantial scientific findings published, and I believe that your statistical methods are a valuable contribution for reconstructions of climate data.

I personally believe that a your responses (as in this post) are not as respectfull and professional as they could be, and I think that with this post you may have actually destroyed a bridge of science-based argumentation which was apparent in the reviews. I think that this post from you was not necessary, and definitely not in the tone that you used. But that is just my opinion.

I have been clear, though you may have missed it. In the post, I said that if you combine the stations as is the West Antarctic trend is 0.16 deg C / decade, and 56% of the West Antarctic grid cells show statistically significant warming for our reconstructions.

Thank you for clarifying the 0.16 C/decade trend that would be obtained for West Antarctica if the temperature readings from the two Byrd stations are considered as-is, without difference in offset.
Indeed I missed that remark in your original post. I think that is a fair result, considering that there is little physical evidence to sustain a decision to see them as totally separate stations.

This trend of 0.16 C/decade would challenge your conclusion that you obtained ‘significant’ different trends for West Antarctica than Steig 09, but I think that the main findings of your paper, that the statistical methods are better, is more important than the results for an application area of Antarctica.
Especially your finding that the satellite records should be taken with a grain of salt, at least for the temporal changes, is illuminating and I would love to see your methods tested on other data records around the planet.

So once again, congrats on your publication, and thank you for adding an important statistical methodology to the interpretation of climate data stream, from satellite and ground stations alike.

I did step up my research on the statistics, and as part of that I still have a few questions on the R code that you published (most specifically, I’d like to know if there are routines that can print the resuls from the ‘recon’ structure in understandable (map or table) form, or if we should write these routines ourselves). I wonder if I should ask specific questions on the R code in this forum, or if I should send email instead.

Thank you for making all your data and methods available for others to investigate. I need to let you know that that is most appreciated.

Ryan,
In your paper, you report a warming trend for Antarctica as a whole of +0.09 +/- 0.1 C, and it that warming is thus not statistically significant. All true, but if the Byrd trick (separating the two stations in the statistical analysis) results in an increase of warming for West Antarctica from 0.1/decade to 0.16/decade as you point out above, then Byrd is also a deciding factor w.r.t. the significance of warming of the continent as a whole.

With that knowledge, would it not be fair to say that the decision to separate the Byrd stations in your statistical analysis created two ‘significance’ claims that would otherwise not exist ?

Not sure where you are getting that number. The continental trend in our paper is 0.06 +/- 0.09 (not statistically significant) and West is 0.10 +/- 0.09 (statistically significant). The statistical significance of neither changes by using Byrd as a single station.

Next, you insist on implying that slapping the two stations together is the “default” and separation is a “trick”. This is entirely backwards. There is no a priori knowledge on how to combine the stations.

Rob, you are so bent on your “null” notion of treating incomplete and non overlapping Byrd AWS and manned as a single thermometer. Perhaps you can point us to your method citations which use your null.

Sorry Ryan, I should have been more accurate with my question and statement.

You stated that if the Byrd station data is merged as a single station that the warming trend with your method and parameter settings from increased from 0.10 to 0.16 C/decade.

It is clear that that trend would make the conclusion of ‘significant’ difference with Steig 09 invalid for West Antarctica.

But also, since West Antarctica comprises something like 20% of the continent’s area (correct me if I’m wrong), one could expect the trend for the entire continent to increase by some 0.01 – 0.015 C/decade, just because of that choice at Byrd.

You write in your paper that your reconstruction finds that “the continental average is not significant at the 5% level (0.06 +/- 0.07 C/decade)”.

Since that is only a 0.01 C/decade trend away from being ‘significant’, the choice of Byrd would at least seriously challenge the conclusion of ‘not significant’ warming for the continent as a whole, or at least reduce that conclusion to a rasor thin margin.

It seems obvious that your conclusions about trends in West Antarctica and conclusions about ‘significant’ differences with Steig 09 are sensitive to the choice of how to treat Byrd data.

That was what I wanted to say.

Once again, I think that your statistical methods are an improvement (especially for data dense areas such as the Peninsula), but it would be good if you could recognize that in very data sparse areas like pre-1980 West Antarctica) station data has to be treated very carefully, or else your method may create significant changes to trends that may not exist in reality.

Maybe Steig used the ‘wrong’ methods but came to the right conclusions, while you may have the ‘right’ methods but came to the wrong conclusions.

Overall, I think if statisticians can work together with climate scientists, rather than trying to refute each others work, that we could benefit from better and more realistic temperature reconstructions.

I cannot get past the point that simply splicing the two Byrd stations together is wrong. You seem to think that it is right. Why? What evidence do you have that you should simply splice them together? You also seem to think that this is the difference between ours and S09. It is not. S09 doesn’t even use the Byrd AWS data at all, and the gridded trend at Byrd has nothing to do with Byrd.

You are assuming things that I do not, because there is no evidence that those assumptions are valid (in fact, the balance of the evidence is that they are not valid).

For starters, if you ever want to go beyond prior science and Steig’s methods of reconstruction, then you need to let go of defensive arguments that compare your methods to Steig’s. So I’ll not respond to your “S09 doesn’t even use the Byrd AWS data at all” sort of remarks. You need to let go of the past and face new challenges, previously unexplored.

One of the new challenges is the sensitivity of your method to data-sparse areas such as West Antarctica and Byrd specifically, which seriously affect conclusions drawn with your methods, as I showed in the post above.

At Byrd, we have the situation that there are two stations, which are spacially very close, but have no temporal overlap. That means that there is no spacial correlation that could give a clue on any potential ‘offset’ (caused by micro climate or sensor differences) between the two stations. Also, there is no third station nearby that has temporal overlap with both, so we cannot fill in the missing temporal data between the two stations, nor calculate the offset based on strong correlation between the three stations.

In such a situation, what do we do to infill the missing temporal data at that location, and what do we choose as an ‘offset’ ?

You can use statistics of correlation from the nearest stations that have a record “temporally”, to obtain a likely ‘estimate’ for the Byrd location. That would be stations that are ‘spacially’ 1000 miles away.

A priori, it is unclear how ‘accurate’ a reconstruction will be from 1000 miles away.

The second way would be to use correlation with the nearest stations physically.
That would be the other Byd station, which is ‘temporally’ a decade or so away.

Now, as I pointed out before, if anyone has ever been to Byrd, or has seen the pictures on Google Earth, it would be very hard to validate ANY offset between two stations being 2.5 km apart on that deserted ice field without a proper physical explanation.

So from a physical, ‘spatial’ (over 2.5 km) point of view, there is no reason to assume that the temperature readings from the two Byrd stations would need to be offset at all. Let alone which direction the offset would need to go.

And from the ‘temporal’ point of view, the only information we have is by interpolations between stations 1000 miles away.

So what do you trust more ? 1000 miles, or a change in sensors over a decade ?

I am still not familiar enough with your R code to incorporate this ‘temporally non-overlapping, but spacially-proximate’ constraint, but I think it would overall greatly enhance realistic reconstruction.

Maybe I should state the question differently :
What do you trust more, statistical correlation with stations over 1000 miles (and different climate zones) or microclimatic differences over 2.5 km on an ice field ?

I do not mean to sound rude, but this is why you need to actually calculate something rather than simply assume.

I trust the interpolations more. Why? Because when I do it using interpolations, and measure the RMS error at entirely withheld stations, I get an average error of ~1.0.

When I don’t use interpolations and splice stations co-located stations together, I get RMS errors exceeding 3.

For example (if you don’t like Scott Base and McMurdo which have a 3 degree difference even though they are 2.5 km apart), let’s go to the South Pole. Up on a plateau, no pesky ocean nearby, negligible glacier movement, nice and flat.

Let’s look at Clean Air (AWS) and Amundsen-Scott (manned base). They are even closer than the two Byrds. If you take the means of the raw data for common points, you get:

Amundsen-Scott: -49.6349
Clean Air: -50.03073

Difference: 0.3958

Just like everywhere else in the world, the absolute temperatures do not match at even nearby stations – or even co-located ones. This is why anomalies are used, because the anomalies do correlate well over vast distances. The surface temperature indices depend on this.

I will not answer any more questions until you have put in more effort than looking on Google maps. Calculate something. Try to show that you can combine raw data from stations 2.5 km apart. Then come back.

I’m sorry, but I will not continue this conversation if all you wish to do is postulate without verifying.

By the way, if you wish to start with a physical reason for this behavior, start with winds.

The winds in Antarctica heat the ice surface due to friction. This is one of the reasons a strong (> 3 degree) gradient can be observed in air temperature as one proceeds from the ice surface to a few meters above the ice surface. Slight differences in sensor height (or extreme, like whether the sensor is at a manned station – where the height is maintained – or an AWS station which can get buried in the snow) can cause massive (in terms of trend) errors when attempting to simply splice two raw data sets together. This means sensors at exactly the same geographic location can show multi-degree differences.

Rob
Posted Feb 15, 2011 at 2:50 AM |
….
Heck, if O’Donnell wants to validate the offset by claiming an urban heat island effect in the manned AWS station

Rob, Byrd AWS (Automated Weather Station) is by definition unmanned.
The issue here is between the manned pre-1975 Byrd station, which presumably was a Stephenson screen or similar shelter, versus the post-1980 Byrd AWS, which was a different sensor in a different type of shelter at a different location (2.5 km away, according to the coordinates, says Ryan).

S09 did not use the AWS data at all in their primary reconstruction, but apparently Ryan et al used it in their cross validation procedure to choose the truncation parameters, whence its (only secondary) relevance to the issue. (See my 2/7 post above and Nic’s reply.)

Anyway, isn’t this thread getting a little “narrow”? 😉 At least on my browser, it’s barely 2″ wide.
Steve: Install Pete H’s CA Assistant app which places comments in chron order. Works on some other blogs as well (Lucia’s.) Makes things way easier.

Steig stated : “shown in the figure (dashed) is an independent infilling of missing data from Byrd station, done by Andy Monaghan (using no satellite data whatsoever, as described in Monaghan et al., 2008, plus new data available through 2009).”

So he was referring to the new data available through 2009 when he mentioned the +0.32 C/decade trend.

Monaghan 2008 does report a significant cooling at Byrd since 1992 (which pretty much undoes the warming before that time), but adds a warning : “Because portions of the Byrd record have been reconstructed, the negative temperature trends may be viewed with skepticism.”

The latest data until 2009 from Byrd shows very significant warming, so it would be interesting to see what would come out of the O’Donnell method if it would be updated with the latest 2009 data…

Monaghan 2008 does report a significant cooling at Byrd since 1992 (which pretty much undoes the warming before that time), but adds a warning : “Because portions of the Byrd record have been reconstructed, the negative temperature trends may be viewed with skepticism.”

To paraphrase your earlier comment:

Then, when (not surprisingly) they obtain a significant offsetdecreasing trend, they try to validate that by handwaving at microclimates and sensor differencesthe uncertainties of the statistical procedures. That is ‘putting the horse behind the wagon’ at best and scientifically dishonestselectively convenient at worst.

Before using Monaghan as a paper with solid statistical analysis, perhaps you might look at the following quote from it:

A reconstruction of Byrd temperature from 1978 to 1997 based on passive microwave data [Shuman and Stearns, 2001, 2002] was obtained from the National Snow and Ice Data Center (http://www.nsidc.org). The passive microwave record matches the AWS record closely for the months in which both are available (r2 = 0.999, n = 150, p < 0.0001), and thus the passive microwave data are considered reliable.

How do you suppose they got such an unrealistically large correlation?

That type of correlation normally occurs when one is comparing records of two sets of data from the same source. Different decimal places could account for the 0.2% of the variance that is missing!!
I have not seen a copy of the Monaghan article. Surely they must comment on this specific finding.

No, they seem to treat this matter-of-factly. My strong suspicion is that they have calculated the correlation on the original raw temperatures and not on anomalies calculated from that data.

The magnitude of the correlation is then a simple reflection that they share the same seasonality without indicating how strong the relative agreement of the two series would be once the seasonality has been accounted for. It sounds impressive, but doesn’t really measure the right quantity.

Roman:
I do not believe that you could get this high of a correlation if there are two different independently generated data series using two different types of measurement devices. The measurement error in the devices alone would create a lower correlation than this. A correlation of 0.999 suggests that there are no differences in the devices and that you would get almost precisely the same measure with a simple transformation of the raw data.

Roman:
I stand corrected. I compared Central Park with West Point and got r=0.996 for the entire record – 1895 to 2010. When I sampled the most recent 180 months I got r=0.997.
When I correlated same month data across the enitre common period I got an average correlation across the 12 months of r=.882. (all using Excel)

Let’s return now to the question of whether O’Donnell et al.’s results actually do represent an improvement over ours.

Steig asks the question “explicitly” then states his case. Are you seriously suggesting that because Steig did not add the phrase ‘….therefore our reconstruction captures the station data better than O’Donnel’ phrase at the end of his argument that Ryan’s statements are unsupported?

“I have known that Eric was, indeed, Reviewer A since early December. I knew this because I asked him. When I asked, I promised that I would keep the information in confidence, as I was merely curious if my guess that I had originally posted on tAV had been correct.”

Other than Ryan’s assertion is there currently any evidence for Steig to be reviewer A? Also, is there any evidence that the reviewer A for one draft was the same person as reviwer A for the next?

I’m sure O’Donnell has checked this before breaking a confidence in such a public forum of course…

“Demeaning” has nothing to do with it. It is not demeaning to call a deceptive tactic “deceptive”. Eric’s actions are the very definition of the word “duplicity”. I have no desire to post any comment (civil or otherwise) on his turf when it is clear he is not willing to play by rules that are in any way civil or fair.

Perhaps you ought to post at RealClimate why Eric would recommend something (indeed, why Eric would INSIST that the editor require us to make the change) and then later attempt to hold that very same change against us.

Or is that okay in your world? If so, you can be quite sure that I will not be visiting your world any time soon.

Are you serious? First, O’Connell’s response wasn’t demeaning although it WAS illuminating. Second, RC has been anything but civil — why play the game on their terms? This board is pretty darned open, they can make whatever point they want here — if in fact they can muster up a coherent legitimate response.

My suspicion is that Steig is slow to respond here because he KNOWS a number of people here can respond to any prevarications promptly and with specific data or quotations refuting them — that he INTENDS to prevaricate but he needs to think and compose more carefully because he doesn’t have the ability to just kill responses here the way he or Gavin do at RC.

“A new reconstruction of Antarctic surface temperature trends for 1957–2006, reported this week by Steig et al., suggests that overall the continent is warming by about 0.1 °C per decade. The cover illustrates the geographic extent of warming, with the ‘hotspot’ peninsula and West Antarctica shown red against the white ice-covered ocean. [Cover image: NASA Goddard Space Flight Center/University of Washington/USGS]”

Barry Woods – perhaps the co-authors of S09 included the remaining reviewers of O10. (I doubt it, but the unfolding story is compatible with such a scenario).

Re reviewers, what can be said of those who let S09 slip through, while failing to notice the meaty material found by Ran and co-authors? Their failure has broad, serious implications for peer review in climate work.

Time and agin, one comes back to the Wegman report (see sidebar for source),

Recommendation 3. With clinical trials for drugs and devices to be approved for human
use by the FDA, review and consultation with statisticians is expected. Indeed, it is
standard practice to include statisticians in the application-for-approval process. We
judge this to be a good policy when public health and also when substantial amounts of
monies are involved, for example, when there are major policy decisions to be made
based on statistical assessments. In such cases, evaluation by statisticians should be
standard practice. This evaluation phase should be a mandatory part of all grant
applications and funded accordingly.

That Steig was a reviewer of O’Donnell et al paper is in clear breach of the AMS regulation regarding the obligation of reviewers, and obviously a very questionable attitude on the editor side:

Obligations of Reviewers in the AMS Scientific Publication Process
…

5. A reviewer should be sensitive even to the appearance of a conflict of interest when the manuscript under review is closely related to the reviewer’s work in progress or published. If in doubt, the reviewer should indicate the potential conflict promptly to the editor.

6. A reviewer should not evaluate a manuscript authored or co-authored by a person with whom the reviewer has a close personal or professional connection if the relationship would bias judgment of the manuscript.

Steig is right on this point. It is absolutely common for an author whose work is being criticized to be asked to review the paper criticizing him. The hope is that the review process will allow the authors to reconcile any minor differences, so that only substantive differences appear in the final article.

The journal’s editors were certainly aware of Steig’s conflict of interest (and, in fact, likely selected him as a reviewer because of it).

The real problem is that Steig has been deliberately misrepresenting himself in his public criticism of the paper, criticizing arguments which he made as a reviewer, and pretending that this was his first opportunity to look at the calculations in ODonnell et al.

In my opinion, Steig simply lacks that mathematic background to fundamentally understand the methodologies that he and Ryan employed. Despite this, he feels that he needs to vindicate himself. The result is some rather desperate flailing on his part, that seems likely to rebound on him.

It will be interesting to see the responses that Revkin gets when he asks about this incident. I hope that, rather than focusing on the fact that Steig was a reviewer of ODonnell (ho hum), he instead focuses on the fact that Steig’s public criticism of ODonnell is blatantly disingenuous given the substance of the peer review interactions between the parties.

Eric has revealed himself as a man who will say obviously false things in the hope of making himself look better.

What isn’t common is for the first authors review to be anonymous and for him to be given first review status and allowed to try and disrupt the paper with 88 pages of nonsense. Eric’s comments to the paper should not have been anonymous and he shouldn’t have been given the leeway he was given. Period. This whole mess could have been avoided if his participation in the review was public.

Now some would argue that that would violate the anonymous reviewer ideology in the first place, but that doesn’t hold water. Of course the author of a paper being challenged is going to be given space for rebuttal! Why would that need to be done in secret?

The paper should have been given to two or three non-involved anonymous reviewers and then also given to Steig for comment. Steig’s comments should have been taken in context only (context being the known bias he would have). What happened here was wrong on many levels.

7. A reviewer should treat a manuscript sent for review as a confidential document. It should neither be shown to nor discussed with others except, in special cases, to persons from whom specific advice may be sought; in that event, the identities of those consulted should be disclosed to the editor.

If the document had been shared with others by reviewer A, this information should have been communicated to the Editor. I would think that the Author would have the right to know that this has occurred and with how many people (although it would be reasonable for the Editor to suppress the names of those specific individuals). Perhaps a question to the editor might be in order.

I don’t have a problem with Steig being asked to review a paper critiquing his analysis. I am more than a bit perturbed that the editor chose to accept criticisms of the volume and vociferousness indicated — that would indicate to me that the original author was being defensive and possibly petty.

I WOULD be interested in a syntactic analysis of the critiques to see if they were all done in the same writing style or if perhaps Steig was collecting criticisms from “The Team” — that WOULD be an ethical violation, would it not?

That Steig was a reviewer of O’Donnell et al paper is in clear breach of the AMS regulation regarding the obligation of reviewers…

“5. A reviewer should be sensitive even to the appearance of a conflict of interest…”

I do not see any ethical problems in Dr. Steig agreeing to review O’Donnell ’10. The conflict of interest is obvious, to Steig and (more importantly) to the Editor who asked for his service. The Editor would be expected to weigh this divergence of interests in evaluating Steig’s reviews.

Ryan O’Donnell says:
February 7, 2011 at 12:16 pm
Before this gets too out of hand, I’ve said before (and I will stand by this statement) that the journal and editor did a commendable job of sorting through everything. An additional reviewer was, indeed, added in the middle of the process to arbitrate, and I believe that Journal of Climate and Dr. Anthony Broccoli did a fine job with this situation.

I would ask that people refrain from criticizing JoC or Dr. Anthony Broccoli.

Still, given the AMS policy, the editors, by presenting Referee A as an implicitly unbiased anonymous reviewer, created a misunderstanding that should never have existed in the first place.

Steig therefore can’t be blamed that his identity was kept from Ryan et al, even if he did then abuse his position while posing as an “impartial” reviewer.

I don’t think there’s any point in attacking Broccoli or J Clime — especially if you want to get results published. They have taken a huge step already in working with O’Donnell et al and that’s to be commended. The more Steig obfuscates and throws a tantrum, the more it hurts him, even with (reasonable) people who want him to be right.

So the biggest complaint is that Steig intentionally forced ODonnell, in a review comment, to use a result that he could later criticize by saying it underestimated the trend. But is it the case that both underestimated the trend and that ODonnell’s use of station data had pitfalls either way, it’s just that Steig’s suggestion was the “most likely”? Not sure what the answer is here. This appears to be another example of dragging scientific arguments out into the open to make a scientist look bad (Oh how surprising!) But I would like at least the scientific complaint to be addressed, if possible.

[Response: I haven’t bothered to go read what is evidently being written about me, but if this is an accurate description um.. you’re kidding right? I’m now being blamed for their writing a lousy paper? Really? If this weren’t so sad it would be hilarious!–eric]
#
66
Dave Walker says:
8 Feb 2011 at 8:02 AM

Non scientist here again.

I have read the piece here in RC regarding Antartic temperatures and also read the pice by a Jeff Id. I do not know who these people are but there seems to be a real disagreement about scientific method and who said what – but its is beyond my understanding.

Mr Id seems somewhat agrieved on a number of points that he feels a very important. One is whether a reviewer of his paper was actually one of the people who’s methods were being challenged (is this correct, is it “normal” practice or does he have a point?). Secondly, he takes issue with processes and statements and the way he has/is being treated.

Any chance that someone could clarify these points for me?

[Response: It would be entirely normal for an editor to send a paper criticizing someone’s work to that person, for their opinion. You just wouldn’t want that opinion to be the deciding factor, which is why normally you’d get several other reviewers; this is presumably the case here. Reviews, however, are usually confidential and anonymous.

As for our ‘treatment’ of Jeff Condon, he hasn’t written anything here lately so I really don’t have any idea what he is talking about.–eric]

[Response: I haven’t bothered to go read what is evidently being written about me, but if this is an accurate description um.. you’re kidding right? I’m now being blamed for their writing a lousy paper? Really? If this weren’t so sad it would be hilarious!–eric]

Wow! “I’m now being blamed for their writing a lousy paper?” What??? Words fail me…

I really think Eric Steig has lost it…he appears to be cracking up. I hope he has the proper support he needs to make it through this apparently traumatic episode in his life.

Now the paper is lousy. Hmm. I suppose Ryan’s critique of the hand waiving was too strong then eh? I didn’t know for certain that Reviewer A was Steig so when I read the initial RC post, it read like more evidence that our initial suspicions were wrong. I assumed that he wasn’t the reviewer who forced us away from TTLS because he criticized our non-usage at RC. Now that we know he pressured us to change methods, then critiqued us for not using the methods we were pushed away from (even though they all got the same answers) it’s crazy.

He’s really just got to settle the heck down and read the math. The story shouldn’t be about extreme personality disorder, just math.

Wow, the recess seems to be over and Eric is figuring out a response… I know its just speculation but… The comment below from RC clearly, in its infantility, looks like afabricated one. And would otherwise clearly have ended up in the bore hole. It seemes to be just necessary to give Eric a chance to make his “points”.

67Dave Walker says:
8 Feb 2011 at 8:02 AM
Non scientist here again.

I have read the piece here in RC regarding Antartic temperatures and also read the pice by a Jeff Id. I do not know who these people are but there seems to be a real disagreement about scientific method and who said what – but its is beyond my understanding.

Mr Id seems somewhat agrieved on a number of points that he feels a very important. One is whether a reviewer of his paper was actually one of the people who’s methods were being challenged (is this correct, is it “normal” practice or does he have a point?). Secondly, he takes issue with processes and statements and the way he has/is being treated.

Any chance that someone could clarify these points for me?

[Response: It would be entirely normal for an editor to send a paper criticizing someone’s work to that person, for their opinion. You just wouldn’t want that opinion to be the deciding factor, which is why normally you’d get several other reviewers; this is presumably the case here. Reviews, however, are usually confidential and anonymous.

As for our ‘treatment’ of Jeff Condon, he hasn’t written anything here lately so I really don’t have any idea what he is talking about.–eric]

“I realized upon careful review of the published paper (O’Donnell et al) that the methods I had suggested as reviewer had certain flaws. So when I went back and tackled these, the outcome was surprisingly closer to our Nature paper. Since I felt responsible in part, for O’Donnell et al being published in its present form, I decided not to communicate my findings to J Clim, in keeping with my good conscience. And frankly, I was surprised that the authors did not examine these suggestions, flawed as they were, in any greater detail at all and simply accepted them. Indeed, as I sat down to take in the whole paper in its published form, (after months of heavy drilling work), its problems became apparently to me immediately. This is perhaps only a reflection of the unfamiliarity of Antarctic climate research on the part of the authors of O’Donnell et al.
.
But the new results were important enough to be communicated so we published them at Realclimate recently, for open discussion. But one of the co-authors bizarrely enough, attacked us violently in our comments section.
.
We, at Realclimate, realize now that the lead author has broken faith with the journal in revealing the identity of its reviewers to a half-crazed public at denier websites. I personally feel enormous regret that I put in so much hard work in reviewing this paper to begin with, even though its findings were hostile to my Nature paper. Scientists do not get any compensation for their peer-review efforts and now my name has been unfairly dragged in the mud. I have been called names and people have issued personal threats. I realize how Ben Santer must have felt. I am now moving J Clim to take remedial, disciplinary action directed at authors of O’Donnell et al 2010.”

Some of the differences are real and correct. You took the example of a single station in your article. This is what I was referring to, you can’t really look at that small of a scale with 7 pc’s and expect a perfect match. The stations information may very easily be shifted nearby the point being examined and can also be reasonably well weighted. The number of PC’s determines the resolution.

On larger regions the patterns will average out if the math is correct but an arbitrary boundary may or may not have perfect representation. I believe that the Ross issue is something that Ryan and Nic would have more expertise with than myself but again if you look at the area weighted and our reconstruction, the similarities are quite evident. We aren’t far off from the actual station data (I have confirmed this with several methods), but IMHO the station position is a more reliable indicator of where the information should be than correlation with noisy and highly spatially correlated sat data. Again, the simple methods are also is difficult to disagree with and if you check them out they may make your case better than you think.

If you take a look at the area weighted link, you can see that some of the trends are more muted, but represent a very similar pattern to what our paper revealed – and IMO a very different one from your original. Just be careful when looking at a truncated least squares method when analysing patterns, especially when the sampling is not spatially even. [edit -keep on trying to sneak in off-topic snark like this, and all of your stuff will go straight to the borehole from now on–understood?]

Eric Steig complains that O’Donnell coauthors should comment at RC rather than at our own blogs. Meanwhile RC deletes or buries any comments. What a joke.

Steig:

If they have scientific points to make, they should make them here.–eric]

Two days earlier, the following comment by Jeff Id was placed in the “Borehole”, described as “off-topic snark”:

Some of the differences are real and correct. You took the example of a single station in your article. This is what I was referring to, you can’t really look at that small of a scale with 7 pc’s and expect a perfect match. The stations information may very easily be shifted nearby the point being examined and can also be reasonably well weighted. The number of PC’s determines the resolution.

On larger regions the patterns will average out if the math is correct but an arbitrary boundary may or may not have perfect representation. I believe that the Ross issue is something that Ryan and Nic would have more expertise with than myself but again if you look at the area weighted and our reconstruction, the similarities are quite evident. We aren’t far off from the actual station data (I have confirmed this with several methods), but IMHO the station position is a more reliable indicator of where the information should be than correlation with noisy and highly spatially correlated sat data. Again, the simple methods are also is difficult to disagree with and if you check them out they may make your case better than you think.

If you take a look at the area weighted link, you can see that some of the trends are more muted, but represent a very similar pattern to what our paper revealed – and IMO a very different one from your original. Just be careful when looking at a truncated least squares method when analysing patterns, especially when the sampling is not spatially even.

[edit -keep on trying to sneak in off-topic snark like this, and all of your stuff will go straight to the borehole from now on–understood?]

The peninsula station smearing is the same effect that occurs when the heavily oversampled bristlecones are included in Mann’s paleo reconstructions.

It is a sore spot with Mann because I have been much more strongly worded with his idiocy/work than anyone including Steve. Honestly, the wording was probably entirely different and I’m sorry I didn’t bother saving it, RC clips everything I write but as far as I recall SNARK is libel on their part!! 🙂

I guess I could understand snipping that single line as off-topic, but the rest of the post is hardly borehole material (as that term would be objectively defined)…but then when have the standards at RC been objective?

And going off-topic myself, many thanks to you and your co-authors for the intelligence to work out what was wrong in the Steig reconstruction, the effort to improve upon it and expand the understanding of the methods, and even more for the perseverance to see the article through into publication. I get the impression sometimes that many papers in this nascent area are just stabs in the dark, and if a poor one is allowed to stand unexamined (I won’t go further off-topic and mention any particular exaMBHple), then it intimidates successors into following its path rather blindly.

I don’t think that Fenton Communications have really got to grips with the Internet Age. When dealing with the MSM, they could act as a gatekeeper and keep control over the message that was broadcast. In the new era, this degree of control is completely illusory. Steig and his colleagues at RC seem to really believe that they can control the message. Fortunately the existence of multiple, independent (and non RC moderated) websites makes that impossible.

FWIW on the few occasions when I have been a reviewer for a paper criticizing my own work, I have signed my review and carefully NOT tried to block it. Usually I ask that certain issues be discussed or conclusions qualified. Tried to improve it.

FWIW on the few occasions when I have been a reviewer for a paper criticizing my own work, I have signed my review and carefully NOT tried to block it. Usually I ask that certain issues be discussed or conclusions qualified. Tried to improve it.

That is my own personal ethic too, Craig.

If Steig is willing to be a reviewer of a work critical of his own manuscript, he should have the cojones to sign his name to the review.

I have a question which I realize invites speculation. The details of this saga seem to break down into two general categories. The first can be summarized as involving various unsavory personal behaviors on the part of Steig (with help from his RC friends). The second category involves the refusal of Steig and his friends to recognize what the O’Donnell paper is really all about. As Ryan points out and we have discussed in the past, the paper is NOT an effort to render a scientific opinion about the trend of the temperature record in Antarctica. Instead, the paper simply shows that, if anyone wants to use the stats that Steig and company did, they should do it properly.

My question is about this second aspect of this (and I realize I am asking people to speculate). Do Steig and company really not understand this about the O’Donnell et al paper? Or do they understand it and are deliberately mischaracterizing the paper in order to try to attack it?

Obviously, neither answer places them in an attractive light. The first would demonstrate incompetence and the second would reflect on their integrity. But I don’t think it appropriate to automatically assume that the answer is the latter. Steve and others have pointed out a whole lot of really sloppy work and sloppy arguments from the team over the years. So I ask the question because I guess the track record is such that the sloppiness shouldn’t reflexively be assumed to be a function of problematic integrity. Maybe they just don’t get it.

“As Ryan points out and we have discussed in the past, the paper is NOT an effort to render a scientific opinion about the trend of the temperature record in Antarctica. Instead, the paper simply shows that, if anyone wants to use the stats that Steig and company did, they should do it properly.”

I think the phrase “they should do it properly” is what is apparently so upsetting to Eric Steig. This must be a monumental embarrassment for him – a group of “outsiders” upstaging his hard work, and all after he was published in Nature with the famous “red tinged” temperature map of Antarctica on the cover. Now, he’s no longer interested in the science, but is in a panic to salvage his reputation. I wonder if some of this bizarre behavior is a result of extreme peer pressure by some of the radical elements in his cabal…sad, really.

When I published my paleoclimate reconstruction, it was specifically to show that leaving out tree rings gave a different result, but the criticism was that it wasn’t “good”–but I didn’t say the endeavor was even possible and clearly stated the limitations of the data. The tactic of criticism is the same here.

Re: John A (Feb 8 18:15),
Ryan,
I’ve been trying to run the script too. I’ve had a few problems, mostly easily solved. But I’m stuck here:
in tsvdRegFn:
D = sqrt(diag(dat$C))
As far as I can see, dat$C is a vector of logicals, which has furthermore just been set to NA. So it gives an error:Error in if (length(data) != vl) { :
Not easy to interpret, but not surprising if dat$C is not a matrix.

So I tried dat$X. But that gave an error too:Error in svd(dat$X, nu = n.eof, nv = n.eof) :
infinite or missing values in ‘x’
In addition: Warning message:
In sqrt(diag(dat$X)) : NaNs produced

I was able to get through with the code on Linux, ignoring the “binary operation” error which is not relevant to the result, as I understand it. I did however have to edit the following lines in the code:

Anyway, it was fun trying this out even though I of course don’t understand the deeper meaning behind the results. Seems plausible that a scientist should easily be able to work with the supplied code.

I missed this . . . but I uploaded a new version of the code with that one line fixed. I’m not entirely certain the reason for the error you describe here, as it seems to be unique to Linux, and I’m not running Linux.

I posted this on the RC thread – don’t know if it will be bore-holed or not:

@80, I’m not sure you do. Originally, they used TTLS, not iridge.

Below is my take on what the controversy boils down to. Two questions requiring only yes/no answers will hopefully clarify the issue.

1) Dr. Steig, were you “Reviewer A” for the paper?

2) In the (I believe 2nd?) round of reviews, did your review contain this paragraph? (The full PDF is available online, I’m sure you’ll have no problem finding it. It’s linked from the Revkin “Antartic Warming” blog entry comments that you were all interviewed for, on top of the 4th page):

* The use of the ‘iridge’ procedure makes sense to me, and I suspect it really does give the best results. But O’Donnell et al. do not address the issue with this procedure raised by Mann et al., 2008, which Steig et al. cite as being the reason for using ttls in the regem algorithm. The reason given in Mann et al., is not computational efficiency — as O’Donnell et al state — but rather a bias that results when extrapolating (‘reconstruction’) rather than infilling is done. Mann et al. are very clear that better results are obtained when the data set is first reduced by taking the first M eigenvalues. O’Donnell et al. simply ignore this earlier work. At least a couple of sentences justifying that would seem appropriate.

I think the reviewer meant Mann et. al. 2007, but that’s really not at issue. If the answer to both of those questions are yes, it seems to contradict your analysis in the paragraph from this post starting with the sentence: Second, in their main reconstruction, O’Donnell et al. choose to use a routine from Tapio Schneider’s ‘RegEM’ code known as ‘iridge’ (individual ridge regression).
In a nutshell, it seems to the somewhat casual observer that the use of iridge vs. TTLS is being encouraged in the review, and criticized in this blog post. Thanks in advance for reading/clarifying.

Well last time I successfully ran some R code was a little over 4 years ago here:https://climateaudit.org/2006/11/23/juckes-and-the-pea-under-the-thimble-1/
For this I did as Ryan described in the post, including downloading R, and got the same error code as John A above. I did get some nice plots though in the process, so it certainly did a lot of successful work leading up to that.

I am pretty sure that if Ryan et al wrote a paper that challenged conclusions in my paper I could find the time and energy to get it to run.

Over at RC Eric Steig has denied the core of Ryan O’Donnell’s statements, in effect he has called Ryan a liar. Yesterday I asked pretty much the same questions as BPW, they were binned (note not Boreholed, just ignored, I imagine I wasn’t alone), the post, along with Steig’s response is below

83 BPW says:8 Feb 2011 at 7:44 PM

Did my questions get snipped/moderated and if so, why? I should have kept a copy of my questions in case they failed to make it through. They were perfectly legitimate questions giving you a chance to explain this issue from your side rather than letting folks like myself simply take O’Donnell at his word that you acted in an unprofessional and potentially dishonest manner. Simply asking you to clarify your position.

1) Were you, as he states, one of the referees on his paper?

2) If so, do you think that the conflict of interest that would seem to come from that being the case is meaningful and if not, why not?

3) Did you, as part of your review, ask that they change their method only to later criticize that method?

Like it or not, if you don’t directly address these accusations, the impression lay people are left with is that the whole thing smacks of dishonest use of peer review.

I am not qualified to suss out the science, but i am qualified to understand O’Donnell’s accusations. I am willing to accept that there is something lost and that he is misrepresenting the situation, but if you waive away these type of questions and quash those who try to ask, what are we left to think?

[i][Response: Perhaps you should try thinking, instead of asking me what to think. Let me turn this question around on you: why do you take O’Donnell at his word? And now he’s my word: His allegations have no basis in fact. Now you have my word against his. Now try thinking,-eric [i]

[Perhaps you should try thinking, instead of asking me what to think. Let me turn this question around on you: why do you take O’Donnell at his word? And now he’s my word: His allegations have no basis in fact. Now you have my word against his. Now try thinking,-eric]

also there was a response just following that saying something like …
“so you werent reviewer A ,great why oh why has it taken so long for you to say so. ”
sadly that post vanished in the 5 minutes i looked away for.

Pete:
I do not read Eric’s response (at #88)at Real Climate that way. He says
“Response: Perhaps you should try thinking, instead of asking me what to think. Let me turn this question around on you: why do you take O’Donnell at his word? And now he’s my word: His allegations have no basis in fact. Now you have my word against his. Now try thinking,-eric”

Besides elsewhere Ryan provided a snippet of an email wherein Eric acknowledged he was Reviewer A.

There was only one reviewer that had 3 inputs, reviewer A. Ryan posted Eric saying that they did not deal with the same issue all 3 times that he submitted it. Pretty much case closed on him being reviewer A.

Following Steig’s “my word” in-line comment, one of the his supporters wrote to say something like “Aha, so you aren’t reviewer A like the deniers claim”. The comment subsequently disappeared, rather than be corrected,.

My sense is that we are back to the status quo before Steig’s “revelations” in Nature. The Peninsula is warming, W. Antarctica may be and the major part of Antarctica probably not and possibly cooling.
Steig deserves credit for trying to link station data to satellite data but a front page article in Nature seems to have been a bit much.

Eric has now promised to post later today at RC addressing the points about being a reviewer – possibly others too, it’s not clear to me which points he refers to.

BTW my direct question on RC “Just to be clear, when you say at #83 “His [O’Donnell’s] allegations have no basis in fact”, are you saying you were not in fact one of the referees on the paper ? ” has gone down the memory-hole.

Some of Ryan’s language, including the original title, breached blog policies and has been edited accordingly. In particular, the former title imputed motive – which is a breach of blog policies and has accordingly been replaced by the new title “Steig’s Trick”, using a term with a lengthy etymology in climate science and at realclimate.

In emails to Ryan and jeff Id, Steig had objected to the former title of the post. I suggested the present title, Steig’s Trick, as a compromise – as this change of title seemed to me to be “a clever way to tackle a problem” (Holdren here or a “a good way to deal with a problem” (realclimate). Steig himself seemed to think that this change of title was a “clever” as he responded to my suggestion as follows:

Hard to believe the Team feels they can win this one. This is really pretty elementary compared to the paleo reconstructions. The four graphics that Ryan presents are devastating and exactly what several persons predicted right off the bat.

I’ve updated Ryan’s today to reflect the following. Steig stated by email today that he did not see the Response to Reviewer A’s Third Review; the amendment of the incorrect reference in the Third Review to the correct references provided in the Response to the Third Review was apparently a coincidence.

However, Steig must have known that Ryan had submitted a response to his Third Review that satisfied the Journal of Climate editor in sufficient measure that he did not further consult with Steig on the matter.

“My recommendation is that the editor insist that results showing the ‘mostly [sic] likely’ West Antarctic trends be shown in place of Figure 3
…
Perhaps, as the authors suggest, kgnd should not be used at all, but the results from the ‘iridge’ infilling should be used instead….”

The review comment is thus admittedly not directed “to the authors,” but it seems a pretty clear recommendation to the editor that the iridge procedure be included in the paper as a requirement of publication. So unless that comment was made by another reviewer…

Also, Steig claims that “To his credit, Ryan has offered to retract these allegations, now that he is a little better acquainted with the facts.” Does the term “these allegations” include this issue of the recommendation/critique regarding the iridge procedure? Which is, it seems the most serious charge.

Re: GaryM (Feb 9 17:29),
Here’s your quote with a little emphasis:“Perhaps, as the authors suggest, kgnd should not be used at all, but the results from the ‘iridge’ infilling should be used instead….”

And indeed, the authors seem to thing iridge is a good idea. Here’s Ryan and NicL.

is there any evidence that the reviewer A for one draft was the same person as reviwer [sic] A for the next?

Huh? Are you kidding? Make them guess who said that?

Why would any intelligent self-respecting editor randomly shuffle the “names” of the reviewers between various stages of a review? There would be no way to properly continue a dialogue with a specific reviewer on a particular aspect of a paper.

Just posted over at Real Climate. I don’t know why I bothered, though.

“…who continue to believe that these people can be trusted to present their scientific results honestly, and who continue to speculate that their may be truth in the allegations made over the years against Mike Mann, Ben Santer, Phil Jones, Stephen Schneider, Andrew Weaver, Kevin Trenberth, Keith Briffa, Gavin Schmidt, Darrell Kaufmann, and many many others, just because they ‘read it on a blog somewhere’

If you still don’t get it, I’d be happy to share with you some of the more, err, ‘colorful’, emails I’ve gotten from O’Donnell and his coauthors.”

Oh, I get it. Speaking of colorful emails…climategate made it clear both sides are willing to play this game to foward their “paranoid worldviews.” I guess this is science?

But I don’t see the reviews from round 4 there. Could you point them out, please? While you’re at it, could you clearly indicate how you obtained permission to publish this confidential material.

Since when do they need permission to publish confidential reviews, whose confidentiality is entirely to protect the intellectual property rights of the original author, and not the reviewer. You’re confusing the reasons for confidentiality of the reviewers, which is to protect the process, from confidentiality of the reviews, which is to prevent other people from “jacking” an idea from another set of authors and publish it themselves while the original work is still in the review process.

If you think about it, when you write a review, you are surrendering the rights to that material to the authors. (Otherwise when you wrote a review you’d become a coauthor or at least get an acknowledgement.) The purpose of the review process is to provide information (free of any strings) that the authors can use to improve their manuscript. When you do this, you lose any rights to that material: It becomes property of the authors to do with as they please.

If you think the journal has restrictions on the further dissemination of this material (outside of getting adopted into and published in the manuscript of course), please point specifically to the Journal of Climate rules that specifically forbid this.

Otherwise, you’ll need to come up with another talking point why we should once again ignore misbehavior from climate scientists.

Here is a comparison of Rev 3 and Rev 4. All text changes are marked up — including totally minor changes. I hope this works for the reader. (Personally, I would primarily trust this to provide pointers to areas of change as it is not obvious how to reliably discern exactly what the old/new text was.)

Perhaps one of the authors can speak authoritatively on a) whether Wm C’s question (about round 4 reviews) has any standing, and b) whether Eric Steig’s disclaimer (based on not having seen these changes) is appropriate.

And also while we’re at it, can we get you on record as agreeing that this is an obligation of all reviewers?

A reviewer should treat a manuscript sent for review as a confidential document. It should neither be shown to nor discussed with others except, in special cases, to persons from whom specific advice may be sought; in that event, the identities of those consulted should be disclosed to the editor.

9. Editors should avoid situations of real or perceived conflicts of interest

and

5. A reviewer should be sensitive even to the appearance of a conflict of interest when the manuscript under review is closely related to the reviewer’s work in progress or published

and I wonder about this one

7. A reviewer should treat a manuscript sent for review as a confidential document.
It should neither be shown to nor discussed with others except, in special cases, to persons from whom specific advice may be sought; in that event, the identities of those consulted should be disclosed to the editor

And while you’re at it…care to comment on the laudable confidentiality afforded to the task of reviewing (sorry, one should simply say rejecting any contrary work) by the Team, as evidenced by the climategate emails, e.g. Briffa’s “I am really sorry but I have to nag about that review – Confidentially I now need a hard and if required extensive case for rejecting.”?

What I told you about making reviews publicly available is correct. There’s no AMS policy against, nor any formal objection to, an author making the contents of anonymous reviews and responses public. If a reviewer provides his or her name, or if there is other information that makes it possible to discern the identity of the reviewer, such information should be redacted unless the reviewer grants permission.

In the context of this, I would think that publishing an anonymous review and speculating as to the identity of the reviewer would be unethical. The author, if making the review public, has a duty to preserve the anonymity of the reviewer.

More at the link, but given that John is a fairly measured person, this is a rocket you know where. As Eli said note the date.

Noted – it was before Steig’s duplicitous trick on 1st Feb 2011, which relied on the audience being unaware of Review A’s comments and identity.

Up to that point, Ryan had ethically maintained Steig’s anonymity. Beyond that point, Ryan was obliged to break anonymity in order to reveal the duplicity of Steig’s tactics and defend his work (and reputation).

I wonder if John would find it unethical for the entire set of authors of the paper being critiqued being the primary reviewers of those who would critique it? I also wonder if it would be considered unethical for more than just the lead author requested to perform the critique.

These people have not been honest in far too many instances IMO to just say gee Ryan was unethical for disclosing a name we already knew. Look at Steig’s latest where he defends climategate over the fact that Ryan pointed out Steig’s convenient positions.

Attempted to post at RC
Eric
“” who continue to believe that these people can be trusted to present their scientific results honestly, and who continue to speculate that their may be truth in the allegations made over the years against Mike Mann, Ben Santer, Phil Jones, Stephen Schneider, Andrew Weaver, Kevin Trenberth, Keith Briffa, Gavin Schmidt, Darrell Kaufmann,” and Hanson. No I do belive climategat E-Mails cleared up all of that nicely. Eric it is the “team” you run with , Tar baby, Pig pen, mud hole, stop and think why a lay person would ever doubt you?? This will not make it past moteration because it does not fit in the echo chamber..

I felt that splitting the year into 4 seasons was a bit odd given that we are talking about Antarctica – especially given the very large amount of monthly missing data – I have no idea what the daily series look like.
Being simple minded, I split it into 2 6 month periods – Light and No-Light. The warming trend at Byrd appears to be pretty dramatic for October thru March, and more modest and less obvious for the dark months of April thru September.

But, and this is a big but, the amount and pattern of missing data is very troubling. My recollection of the discussions a few years ago on how these averages were calculated would make me very nervous about building a strong argument about what is or is not happening in Western Antarctica. Infilling such a series seems a very dicey thing to do.

I have penned some thoughts on what O’Donnell et al. (2010) teaches about peer review in the field of climate science. If of interest, they can be read as Comment #68919 at Lucia’s Blackboard. My conclusion: what the case shows is something in the middle. Peer-review comes across as neither pristine, nor defective.

Cross-posted at 11:15am at RealClimate (“O’Donnellgate”) and ClimateAudit (“Steig’s Trick”).

I’m not a scientist but have read and appreciated The Hockey Stick Illusion, and am a regular reader of this and other blogs. As I understand it neither Steve McIntyre nor Ryan O’Donnell is claiming they have better results than Mann, Steig & the team. Rather they are saying, “your methodology is flawed, so the results can’t be relied upon”.

The article incudes the following paragraph –
“Steig’s team found the mathematical relationships between the weather station data and satellite data, tested them, and then used them to go back in time to estimate temperatures across the continent back to 1957. Their statistical model has now been validated by an ice core drilled into the Rutford ice stream in West Antarctica by the British Antarctic Survey, from which temperature records can be measured. That independent work also came up with a warming of 0.17C a decade for the region, and stretched the trend back to at least 1930.”

I haven’t seen any mention of this point in any of the various recent posts and wonder if Ryan or one of his colleagues could comment on whether it does or doesn’t validate either Steig’s work or O’Donnell et al’s work.

I tried running your code as you described above. I used R10 Code.txt as opposed to R10 Script (old).R. Is that correct? I also had to download aws.Rdata and manned.Rdata. Then I got a message “cannot open file” READER_groundstations.txt.”” Which I cannot find on the website. I also tried R10 Script (old).R and got the same message.

Re: B. Kindseth (Mar 3 14:22),
BK, there’s a function call in there called downData() which has been commented out. If you restore that, it will fetch the files (once you have them, you can comment it out again). The files come from Eric Steig’s site.

[…] at Climate Audit and other places, in which he broke with the confidentiality usually expected to reveal that Eric Steig had been one of the reviewers of a paper (I’ll update with a link to the […]